Expert System for Industrial Waste Recycling In Road Construction

By Daniel J. Fonseca, Assistant Professor,

Gary P. Moynihan, Professor, and Eric P. Richards, Graduate Research Assistant

Department of Industrial Engineering The University of Alabama Tuscaloosa, AL

Prepared by

UTCA

University Transportation Center for Alabama The University of Alabama, The University of Alabama in Birmingham,

and The University of Alabama at Huntsville

UTCA Report 03116 May 1, 2004

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Technical Report Documentation Page 1. Report No 2. Government Accession No. 3. Recipnt Catalog No.

5. Report Date May 2004

4. Title and Subtitle Expert System for Industrial Waste Recycling in Road Construction

6. Performing Organization Code

7. Authors Daniel Fonseca, Gary Moynihan, and Eric Richards

8. Performing Organization Report No. UTCA Report 03116 10. Work Unit No. 9. Performing Organization Name and Address

Department of Industrial Engineering The University of Alabama Box 870288 Tuscaloosa, AL 35487-0288

11. Contract or Grant No. HPP-1602(524)

13. Type of Report and Period Covered Final Report: 8/16/2003 – 5/1/2004

12. Sponsoring Agency Name and Address University Transportation Center for Alabama Box 870205, 271 H.M. Comer Hall The University of Alabama Tuscaloosa, AL 35487-0288

14. Sponsoring Agency Code

15. Supplementary Notes

16. Abstract It is estimated that 4.6 billion tons of non-hazardous solid waste materials are produced annually in the United States. Their potential for use in the construction of highways and roads suggests that valuable benefits in terms of economic and environmental gains are possible. This project deals with the development of a computer-assisted tool, i.e., an expert system to help manufacturers assess and analyze their industrial residuals as a potential road construction material. Expert systems have been defined as consulting systems that simulate the problem-solving ability of human experts through the use of expertise drawn from an information base and specific rules employed to interpret such knowledge. With the abundance of foundries in and around the vicinity of the city of Birmingham, AL., several non-hazardous solid waste materials were available for analysis. Additional waste materials such as reclaimed asphalt pavement and fly ash were selected due to their common use as recycled material in the United States. The project included five main phases. The first phase consisted of a comprehensive literature review of the problem domain. The identification and data acquisition on key residuals in the foundry industry represented the second phase. Once the collected information was logically organized, identification of potential road construction applications for solid industrial residuals had to be investigated. This phase detailed the chemical and physical properties needed to determine the potential uses of industrial residuals. The fourth phase consisted of coding the heuristics into a format that a computer could interpret. This was accomplished through the use of an object-oriented software shell, Level5 Object. The last phase of the project involved the verification and validation of the developed prototype system. Fifty-one unit tests and thirteen characterization tests were performed to ensure the accuracy of the system. Once the system verification was complete, the system’s recommendations were successfully validated through test cases and a face validation with domain experts. 17. Key Words Expert system, industrial residuals, road construction, material recycling

18. Distribution Statement

19. Security Classification (of this report) Unclassified

20. Security Classification (of this page) Unclassified

21. No of Pages 22

22. Price

Form DOUSDOT Form 1700.7 (8-72)

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CONTENTS

Contents ......................................................................................................................... iii List of Tables ................................................................................................................. iv List of Figures ................................................................................................................ iv Executive Summary ....................................................................................................... v 1.0 Introduction ............................................................................................................. 1 1.1 Background .......................................................................................................... 1 1.2 Project Objective and Approach .......................................................................... 2 2.0 Methodology ........................................................................................................... 4 2.1 Data Collection .................................................................................................... 4 2.2 Fly Ash ................................................................................................................ 4 2.3 Non-ferrous Slags ............................................................................................... 5 2.4 Steel Slag ............................................................................................................ 6 2.5 Blast Furnace Slag .............................................................................................. 7 2.6 Reclaimed Asphalt Pavement ............................................................................. 7 2.7 Knowledge Engineering ..................................................................................... 8 2.8 Environmental Screening ................................................................................... 8 2.9 Preliminary Application Analysis ...................................................................... 9 2.10 Detailed Application Analysis .......................................................................... 10 2.11 System Design .................................................................................................. 11 2.12 System Architecture ......................................................................................... 11 2.13 System Validation ............................................................................................ 12 3.0 Use of the System .................................................................................................. 14 3.1 Input to System .................................................................................................... 14 3.2 System Processing ........................................................................................... 20 3.3 Output of System ................................................................................................. 21 4.0 Conclusions .......................................................................................................... 22 4.1 Comments on the Project .................................................................................... 22 4.2 Recommendations for Future Work ................................................................... 23 5.0 References ............................................................................................................ 24 6.0 Acknowledgements ............................................................................................... 25

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List of Tables Number Page

2-1 Fly ash classes and properties ...................................................................... 5 2-2 Constituent and oxide compositions of non-ferrous slags ........................... 6 2-3 Steel slag constituents and oxide compositions ........................................... 6 2-4 Blast-furnace slag constituents and compositions ....................................... 7 2-5 Maximum concentration of contaminants for the toxicity characteristic .... 10

List of Figures Number Page

3-1 Initial screening display .............................................................................. 14 3-2 Ignitability, corrosiveness, and reactivity screening ....................................... 15 3-3 Toxicity characteristics screening ............................................................... 16 3-4 Oxide composition screen ........................................................................... 17 3-5 First physical properties screen ................................................................... 18 3-6 Second physical properties screen .............................................................. 19 3-7 AASHTO M 145-91 characterization test .................................................. 20 3-8 Report screen .............................................................................................. 21

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Executive Summary

It is estimated that 4.6 billion tons of non-hazardous solid waste materials are produced annually in the United States. Their potential for use in the construction of highways and roads suggests that valuable benefits in terms of economic and environmental gains are possible. Although several states have recycling plans dedicated to such ventures, Alabama does not currently possess a tool to bring expertise from personnel in state and local highway agencies, construction contractors, and consultants into one location to assess non-hazardous materials for recycling and use. This project suggested the use of a computer-assisted tool, such as an expert system. Expert systems have been defined as consulting systems that simulate the problem-solving ability of human experts through the use of expertise drawn from an information base and specific rules employed to interpret such knowledge (Ignizio,1991). With the abundance of foundries in and around the vicinity of the city of Birmingham, AL, several non-hazardous solid waste materials were available for analysis. Additional waste materials were selected in the initial analysis due to their regular use nationwide. The system includes the following residuals: fly ash, non-ferrous slags, steel slag, blast furnace slag, and reclaimed asphalt pavement. These residuals have a wide variety of potential road construction applications ranging from granular and embankment material to aggregate in Portland cement concrete. Initial screening had to be developed to comply with specific Environmental Protection Agency regulations and standards. The system uses these rules to determine whether a waste is hazardous or not. Following the positive non-hazardous determination, the system requires user input to assess the materials chemical and physical composition. After the expert analysis is complete, the user is provided a report detailing potential application areas for the waste. Expert systems are well-equipped to handle problems of this complexity in a structured and logical manner. The capability of implementing the system via the Internet allows a wider range of users across Alabama. The system can also be extended to any number of possible application areas in the future. The use of such a system does not diminish the need for materials characterization data, or the judgment of experienced professionals. However, it does provide a rational and efficient tool to access the potential utilization of industrial solid waste for appropriate, cost-effective applications. The developed system provides the state of Alabama with an innovative tool to use in industrial waste recycling programs.

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1.0 Introduction 1.1 Background In recent years, the public and government have been major driving forces in promoting the recycling of waste products and materials. As a result, there has been a rapidly accelerating trend towards recycling agricultural, industrial, chemical, and domestic residuals by both private and public organizations. State highway agencies across the country are currently advocating incorporation of usable residual materials into the highway system wherever possible (Collins and Ciesielski,1994). The U.S. Environmental Protection Agency (EPA) estimates that the U.S. generates roughly 13 billion tons of non-hazardous waste each year. Waste from manufacturing accounts for more than half of these 13 billion tons, with mining, oil and gas drilling, and agriculture contributing large amounts as well (ASCE, 2003). The potential use of non-hazardous solid waste in the construction of highways, roads, and bridges suggests that valuable benefits in terms of economic and environmental gains are possible. However, a major obstacle in the identification of possible application areas for waste materials is the lack of expertise in assessing non-hazardous materials for recycling and re-use among personnel of state and local highway agencies, construction contractors, and consultants. One possible solution to overcome this obstacle is the use of computer-assisted tools such as expert systems. Experts systems have been defined as consulting systems that simulate the problem-solving ability of human experts through the use of expertise drawn from an information base and specific rules employed to interpret such knowledge (Ignizio,1991). There are different paradigms used to represent knowledge in an expert system; rules being the most popular of all representation schemes. Knowledge can also be expressed in frames, networks, and logical predicates. Rules are If-Then statements which generate conclusions once the validity of specific facts (premises) have been verified (Badiru,1992). For example, the notion of the entity “automobile” can be represented in a knowledge base by the use of the rule: if the object has four tires, an internal combustion engine, and a running speed above 50 mi/hr, then the object is an automobile. Expert systems are structured in three distinct components. The knowledge base is a set of rules about the problem domain, supplied by an expert or obtained through in-depth research. The working memory carries out the tracking of what has been concluded or learned at any stage of a particular consultation. The inference engine evaluates what is true at any given time in the working memory and the knowledge base, resolving conflicts when necessary (Ignizio,1991). A variety of environmental expert system applications have been developed, primarily dealing with pollution problems. A few expert system applications have been oriented to the management of solid waste in the foundry and mining industries (Lester et al., 1999; Moynihan et al., 2000). However, besides the development of a prototype expert system to identify potential road construction application areas for gypsum sub-products, the value of expert system

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technology for analysis of industrial waste residuals for application to highway and bridge construction has yet to be determined (Fonseca et al., 1997). Conventional expert systems tend to be isolated systems. They are normally used for off-line analysis within a single facility. An important consideration is the distribution of the automated expertise to other locations where it may be needed. One potential solution is to provide expert system access via the internet. The Internet has become an invaluable tool for rapid communication and information dissemination. Combining it with the technical expertise of an expert system is a reasonable approach. Several such Internet-based expert systems have been described in the recent literature (Angeli,1999). 1.2 Project Objective and Approach The study addresses the applicability of expert systems to provide recommendations for recycling industrial wastes as highway/bridge construction materials. The objective of the research was to develop a microcomputer-based expert system to assist in the screening of industrial residuals for possible highway construction applications. An Internet-based expert system was developed to demonstrate proof of this concept. The system’s knowledge base focused on a subset of Alabama manufacturers. The knowledge base was constructed by encapsulating the heuristics contained in the literature and applied by experts to determine the potential value of a particular waste material in different roadwork applications. The prototype system provides a baseline for further expansion and refinement. It is viewed as an initial step toward assisting Alabama industry in better meeting government pollution regulations, as well as indicating economic opportunities for these companies within the transportation sector. One of the primary industries in the vicinity of the City of Birmingham is the foundry industry. According to the 1997 Economic Census by the U.S. Census Bureau, Birmingham has 27 foundries with total employment numbers surpassing 5,300 people. These foundries were broken into different ferrous metal and non-ferrous metal categories. Of the 15 ferrous metal foundries, 9 were iron foundries, 5 were steel foundries, and one was a steel investment foundry. The remaining 12 foundries were non-ferrous metal foundries. In addition to the foundries, the city of Birmingham has 46 companies that primarily deal with metal manufacturing. This group includes iron, steel, and ferrous alloy manufacturing and mills, along with steel product manufacturing from purchased steel. This wealth of resources led to the use of the foundry industry as the foundation for the developed expert system. This foundation was further extended to the inclusion of the power generating industry and specific recycling operations. The project dealt exclusively with industrial waste materials originated from combustion residuals, recycling processes, foundry waste, and mill tailings. The ultimate goal of the system is to provide non-experts with a tool for screening residual materials for potential use in the construction of highways and other civil applications. The main goal of the constructed microcomputer-based system is to incorporate the knowledge contained in the published literature on material usage for highway construction and on the experiences of a number of agencies. This knowledge encapsulation process had to be carried out systematically to consider all of the different key factors in the analysis. Therefore, the first step in addressing this problem was to identify major physical and chemical material characteristics required in the different

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application areas through an extensive literature search of the publications of the American Association of State Highway and Transportation Officials (AASHTO), and the Federal Highway Administration (FHWA). The knowledge obtained was then organized and analyzed in a logical fashion. From this analysis, the initial set of inference rules was constructed, the system architecture defined, the material screening scheme conceived, and the graphical displays identified. The formal knowledge representation was then translated into the selected development tool. The final step was the validation of the prototype system which was performed by faculty members in the Civil and Environmental Engineering Department at The University of Alabama.

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2.0 Methodology The methodology used during the project was broken down into five distinct phases: data collection, knowledge engineering, system design, system development, and system validation. 2.1 Data Collection During the first phase of the project, data was collected on the nature and quantities of industrial solid waste generated in the state. The search covered major waste-generating regions of Alabama (i.e. mining and foundry facilities in the vicinity of the City of Birmingham). Also, major physical and chemical material characteristics of different highway and bridge construction areas were identified through a literature search of the publications of AASHTO and FHWA. Next information was gathered concerning the environmental properties of material residuals (i.e., ignitability, corrosiveness, reactivity, and toxicity) which may determine the waste’s suitability for road construction applications. This information was collected from the EPA. After the identification of potential industries producing solid industrial waste, specific residuals from their processes had to be identified as being candidates for analysis. Given the nature of the state’s industries, the residuals selected in this project were fly ash, non-ferrous slag, steel slag, and blast furnace slag. Due to the notoriety and wide use of reclaimed asphalt pavement (RAP), it was also included in the initial study. RAP is the most common residual used in road and bridge construction (Collins and Ciesielski,1994). The potential uses of these solid residuals ranged from embankments and fills to aggregate. 2.2 Fly Ash Fly ash is the finely divided mineral residue resulting from the combustion of ground or powdered coal in electric generating plants (American Society for Testing and Materials Standard C 618, [ASTM C 618]). The most common type of coal burning furnace is the dry-bottom furnace (Turner Fairbank Highway Research Center, 2004). In 1996, approximately 16.2 million tons of fly ash were used. Of this total, 13.3 million tons, or approximately 22% of the total quantity of fly ash produced, were used in construction-related applications. Alabama currently uses fly ash in Portland concrete cement (PCC) and flowable fill. Possible civil applications of fly ash are cement production and/or concrete products, structural fills or embankments, stabilization of waste materials, road base or sub-base materials, flowable fill and grouting mixes, and mineral filler in asphalt paving. Fly ash is used in many construction applications because it is a pozzolan, meaning it is a siliceous or alumino-siliceous material that, when in a finely divided form and in the presence of water, combines with calcium hydroxide (from lime, Portland cement, or kiln dust) to form cementitious compounds (FHWA, 1995). The use of fly ash in PCC is widely common. For fly ash to be used in PCC, it must meet the requirements of the ASTM C 618. Two classes of fly ash

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are defined in the ASTM C 618: Class F fly ash and Class C fly ash. Class F fly ash is produced from burning anthracite and bituminous coals. This fly ash has siliceous or siliceous and aluminous material, which itself possesses little or no cementitious value, but in a finely divided form and in the presence of moisture, chemically reacts with calcium hydroxide at room temperatures to form cementitious compounds (University of Wisconsin-Madison, 2002). Class C fly ash is normally produced from lignite and subbituminous coals, and usually contains significant amounts of calcium hydroxide or lime. This class of fly ash, in addition to having pozzolanic properties, has some cementitious properties (ASTM C 618-99). Table 2-1 indicates the chemical and physical properties needed to determine the class of fly ash.

Table 2-1. Fly ash classes and properties

Fly Ash Class Properties Class F Class C

SiO2 + Al2O3 + FeO3, min % 70.0 50.0

SiO3, max % 5.0 5.0

Moisture Content, max % 3.0 3.0

Loss on Ignition (LOI), max % 5.0 5.0

2.3 Non-ferrous Slags Approximately 10 million tons of non-ferrous slag are produced annually from thermal processing of copper, lead, zinc, nickel, and phosphate ores (Collins and Ciesielski, 1994). These slag are produced in one of two forms: granulated or air-cooled. As of 1994, only four states were conducting research on the possible uses of non-ferrous slag in road construction applications. Possible applications areas have been identified as asphalt and concrete mixtures, along with road base materials. Processing of non-ferrous air-cooled slag for use as aggregate involves conventional crushing and screening to meet the specified gradation requirements. Granulated slag particles are generally of fine aggregate size and may require blending with other suitable material to satisfy specified gradation requirements. One reason for the lack of research concerning this residual is the remote geographic locations where they are produced (Turner Fairbank Highway Research Center, 2004). However, this is not the case when considering the City of Birmingham. Alabama does not currently use non-ferrous slag in any road construction applications. The principle constituents and oxide compositions of the various non-ferrous slag can be found in Table 2-2. 2.4 Steel Slag It is estimated that approximately 7.7 to 8.3 million tons of steel slag are used each year in the U.S. (The Turner Fairbank Highway Research Center, 2004). Alabama is cited as using steel slag as aggregate. Steel slag is formed when lime flux reacts with iron ore, scrap metal, or other ingredients in a steel furnace. Steel slag consists of a fused mixture of oxides and silicates, mainly calcium, iron, un-slaked lime, and magnesium (Collins and Ciesielski,1994). Currently, all steel is made in integrated steel plants using a version of the basic oxygen process, or in specialty steel plants, using an electric arc furnace process. The steel slag produced during the primary stage of steel production is referred to as furnace slag or tap slag. This is the major

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source of steel slag aggregate (Turner Fairbank Highway Research Center, 2004).

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Table 2-2. Constituent and oxide compositions of non-ferrous slags

Composition (%) Constituent Copper Slag Nickel Slag Phosphorus Slag

SiO2 36.6 29.0 41.3

Al2O3 8.1 trace 8.8

Fe2O3 - 53.06 -

CaO 2.0 3.96 44.1

MgO - 1.56 -

FeO 35.3 - -

K2O - - 1.2

MnO - trace -

P2O5 - - 1.3

SO3 - 0.36 -

The key for steel slag is the recovery process. The slag from the furnaces is processed to recover all metal to be reused within the manufacturing process. The non-metallic slag which remains is then crushed and screened for possible aggregate use; this material is called steel slag aggregate. Table 2-3 depicts the constituents and compositions of oxides found in steel slag.

Table 2-3. Steel slag constituents and oxide compositions

Constituent Composition (%)

CaO 40-52

SiO2 10-19

FeO 10-40 (70-80% FeO, 20-30% Fe2O3)

MnO 5-8

MgO 5-10

Al2O3 1-3

P2O5 0.5-1

Property Value

Na2O Soundness Loss, % <12

2.5 Blast Furnace Slag Approximately 15.5 million tons of blast furnace slag are produced annually in the United States (Mineral Commodities Summary, 1993). Alabama does use blast furnace slag, but for only uses as an aggregate. Blast furnace slag is a non-metallic co-product in the production of iron, iron ore, iron scrap, and fluxes, along with coke. Blast furnace slag has a number of different forms as a result of numerous methods used to cool the molten slag. These forms include: air-cooled blast furnace slag, expanded or foamed slag, pelletized slag, and granulated blast furnace slag. Estimates are that approximately 90 percent of the slag produced in the United States is air-cooled blast furnace slag (Turner Fairbank Highway Research Center, 2004). This figure will certainly increase in the future because of the growing movement towards the palletizing procedure.

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Air-cooled blast furnace slag is widely used in Portland cement concrete, asphalt concrete, concrete, asphalt, and road bases. Its main application in these areas is as an aggregate. Alabama has used blast furnace slag in asphalt concrete pavements (Collins and Ciesielski, 1994). Table 2-4 illustrates the constituents and oxide compositions found in blast-furnace slag.

Table 2-4. Blast-furnace slag constituents and compositions

Constituent Composition (%)

CaO 34-43

SiO2 27-38

Al2O3 7-12

MgO 7-15

FeO or Fe2O3 0.2-1.6

MnO 0.15-0.76

Property Value

Na2O Soundness Loss, % <12

2.6 Reclaimed Asphalt Pavement It is estimated that 50 million tons of reclaimed asphalt pavement (RAP) is generated annually (Collins and Ciesielski,1994). It is used by 49 states in some form for road construction applications. RAP generally refers to the removed and/or reprocessed pavement materials which contain asphalt and aggregates. Alabama uses RAP as aggregate generated from paving and building debris applications. The potential uses as an aggregate are unbound aggregate base, and sub-base and shoulder aggregate. Other states use RAP in a number of other applications such as: hot-mix asphalt paving mixtures, cold mixes, in-place mixes, stabilized base course, and open-graded drainage courses (Collins and Ciesielski,1994). In 2001, the U.S. Department of Transportation spent approximately $19,940,000 using RAP as a viable aggregate substitute for scarce bituminous resources (FHWA, 2004). A major concern with RAP is that its properties are reliant upon the properties of the constituent materials and asphalt concrete in which it is used. Also, the number of times the material is recycled increases the opportunity for contaminant material to become integrated. Significant processing and quality inspections need to be conducted to insure the products’ useful and safe performance. 2.7 Knowledge Engineering In the knowledge engineering phase, the collected data was analyzed and logically organized so that it could be represented through If-Then statements or rules. These rules were constructed from cited technical publications. Three sets of heuristics were produced during this phase: (a) heuristics for environmental screening of the residuals, (b) heuristics of the preliminary (broad) application analysis, and (c) heuristics for the detailed application analysis.

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2.8 Environmental Screening The first set of rules was developed to assess the ignitability, corrosiveness, reactivity, and toxicity properties of the materials. Guidelines and specifications dictated by widely adopted EPA regulations constituted the basis for these rules. For further investigation, refer to the following Sections of US Code: 40 CFR 261.21, 40 CFR 261.22, 40 CFR 261.23, and 40 CFR 261.24. Hazardous waste is any solid waste that exhibits any of the known hazardous characteristics as listed by the EPA. According to the EPA, ignitability has the code D001 within regulation 40 CFR Part 261.21. If a solid waste meets any of the following criteria, it is classified as a hazardous waste due to ignitability:

1. A liquid that has a flash point of less than 140o

F as determined by a Pensky-Martens closed cup tester using ASTM method D-93-70 or D-93-80;

2. A solid, under standard temperature and pressure that can cause fire through friction, absorption of moisture, or spontaneous chemical changes and burn vigorously and persistently that is creates a hazard;

3. An ignitable compressed gas as defined by the Department of Transportation in 49 CFR 173.300; or,

4. An oxidizer as defined by the Department of Transportation in 49 CFR 173.151. Corrosiveness code is D002 within 40 CFR Part 261.22. A solid waste that meets any of the following criteria is considered to be hazardous due to corrosiveness:

1. An aqueous liquid that has a pH of 2 or less or 12.5 or more; or, 2. A liquid that corrodes steel at a rate of 6.35 mm or more per year as determined by the National Association of Corrosion Engineers.

The EPA code for reactivity is D003. Reactivity is called out in regulation 40 CFR Part 261.23. A solid waste is considered hazardous due to reactivity if it meets any of the following criteria:

1. Instability and readiness to under to violent change; 2. Violent reactions when mixed with water; 3. Formation of potentially explosive mixtures when mixed with water; 4. Generation of toxic fumes in quantities sufficient to present a danger to human health or

the environment when mixed with water; 5. Cyanide or sulfide waste which generates toxic fumes when exposed to acidic conditions; 6. Ease of detonation or explosive reaction when exposed to pressure or heat; 7. Ease of detonation or explosive decomposition or reaction at standard temperature and

pressure; or, 8. Defined as a forbidden explosive by the Department of Transportation.

The last characteristic of a hazardous waste considered in the study is its level of toxicity. The toxicity code is different from the others’ mentioned. A solid waste whose extract under the test procedure specified under 40 CFR Part 261.24 contains one or more constituents at concentrations greater than those in Table 2-5 is considered as toxic.

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Table 2-5. Maximum concentration of contaminants for the toxicity characteristic

EPA Hazardous Waste Number Contaminant Regulatory

Level (mg/L) EPA Hazardous Waste No.

Contaminant Regulatory Level (mg/L)

D004 Arsenic 5.0 D032 Hexachloro- benzene 0.13

D005 Barium 100.0 D033 Hexachloro- butadiene 0.5

D018 Benzene 0.5 D034 Hexachloro-ethane 3.0

D006 Cadmium 1.0 D008 Lead 5.0

D019 Carbon tetrachloride 0.5 D013 Lindane 0.4

D020 Chlordane 0.03 D009 Mercury 0.2 D021 Chlorobenzene 100.0 D014 Methoxychlor 10.0

D022 Chloroform 6.0 D035 Methyl ethyl ketone 200.0

D007 Chromium 5.0 D036 Nitrobenzene 2.0

D023 Cresol, o- 200.0 D037 Pentra-chlorophenol 100.0

D024 Cresol, m- 200.0 D038 Pyridine 5.0 D025 Cresol, p- 200.0 D010 Selenium 1.0

D026 Cresol 200.0 D011 Silver 5.0

D016 2, 4-D 10.0 D039 Tetrachloroethylene 0.7

D027 Dichlorobenzene, 1, 4- 7.5 D015 Toxaphene 0.5

D028 Dichloroethane, 1, 2- 0.5 D040 Trichloroethylene 0.5

D029 Dichloroethylene, 1, 1- 0.7 D041 2, 4, 5-Trichlorophenol 400.0

D030 Dinitrotoluene, 2, 4- 0.13 D042 2, 4, 6-Trichlorophenol 2.0

D012 Endrin 0.02 D017 2, 4, 5- TP (Silvex) 1.0

D031 Heptachlor (and its epoxide) 0.008 D043 Vinyl chloride 0.2

2.9 Preliminary Application Analysis A second set of rules was constructed to generate a list of possible general civil application areas for non-hazardous residuals based on their chemical composition and physical properties. The principal source of knowledge employed to generate such rules was the AASHTO’s Standard Specifications for Transportation Materials and Methods of Sampling and Testing (1995). After identification of the solid waste residuals to be included in this study, the corresponding road construction applications had to be investigated. The possible application areas were noted after an extensive literature review given the aforementioned solid waste residuals. The system leads to one or more of eight possible general application areas within the following AASHTO standards:

1. Admixture in Portland cement concrete class C (AASHTO M 295-86). 2. Admixture in Portland cement concrete class F (AASHTO M 295-86). 3. Filler for bituminous paving mixtures (AASHTO M 17-83). 4. Blended cement (AASHTO M 240-85).

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5. Drainage filler material (AASHTO M 17-88). 6. Granular material for control of pumping beneath pavements (AASHTO M 155-87). 7. Microsilica for concrete (AASHTO M 307-91). 8. No possible application in highway construction.

2.10 Detailed Application Analysis The final set of heuristics performs detailed analysis on material properties, and leads to specific (individual) application areas. These were developed according to standard AASHTO specifications. The system follows heuristics to generate one or more of the following five specific application areas:

1. Material for embankment and subgrade (AASHTO M 145-91). 2. Material for embankment and subgrade with special consideration (AASHTO M 14591). 3. Fine aggregate for Portland cement concrete (AASHTO M 6-93). 4. Coarse aggregate for Portland cement concrete (AASHTO M 80-87). 5. Fine aggregate for bituminous paving mixtures (AASHTO M 29-83).

2.11 System Design During the system design phase, several requirements and considerations were identified to meet the objectives of the study. The following issues guided the design and development of the system:

• A primary requirement was that the system be portable (microcomputer based). • The system had to provide a friendly interface and be relatively easy to use. Although

the system was designed to access much of the required data from external databases when needed, it has to be capable of requesting required information from the user in a friendly and easy-to-understand manner, as well as present its results in a clear and concise manner. Future versions of the system will be provided with higher capabilities when considering interaction with external databases.

• The user should not encounter any conflict or ambiguity during the consultation or at the moment when the final recommendations are displayed. The user should also assume a measure of assurance with the conclusions provided by the system.

• It was assumed that the user is aware of, or can obtain, information on material properties (physical and chemical), while possessing little or no knowledge pertaining to possible construction applications for the residuals.

The need for friendliness of user interface and versatility for potential accessing external databases led to the selection of Level5 Object – an expert system shell that provides the user with a flexible inference engine and knowledge paradigm – for the system’s software platform. In addition, dBase III for Windows was used for the development of local databases linked to the knowledge base. The system was developed to be executable on an IBM-compatible microcomputer with a Pentium processor.

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2.12 System Architecture The system architecture consists of three major components that are constructed on a modular basis: the databases, the knowledge bases, and the output generator. The database described earlier contains all the pertinent information concerning the chemical and physical characteristics of the residual under consideration, as well as general data on its structure, deposit location, and generated quantity. Only the physical and chemical characteristics of the residual are utilized to evaluate its potential applications. The other information is used to qualitatively characterize and identify the residual. The knowledge bases contain the encoded knowledge needed for performing the analysis as well as making the final recommendations. The following knowledge bases are included in the system:

• Initial environmental screening. This knowledge base analyzes data on the toxicity, reactivity, corrosiveness, and ignitability nature of the residuals to determine whether the material is non-hazardous or has hazardous characteristics. This initial analysis is carried out according to the guidelines and specifications dictated by widely adopted regulations, specifically the Environmental Protection Agency’s guidelines for identifying hazardous waste materials (EPA, 2004).

• Preliminary (broad) application analysis. This analysis requires selected chemical composition and physical properties data to generate a list of possible general application areas. Additional standard test methods are specified in order to collect the necessary data to prove/disprove application viability. The principal source of knowledge employed to in the construction of the system was the AASHTO’s Standard Specifications for Transportation Materials and Methods of Sampling and Testing

(1995). • Detailed application analysis. This section of the system performs detailed analysis of

material properties and makes recommendations for specific (individual) application areas.

The output generator consists of a series of procedures that create a data file with the most relevant information on the characterization properties of the residual, as well as the system’s final recommendations on the residual’s potential possible applications in highway construction. The inclusion of the properties data on the output report provides a means for verifying the input data as well as documenting such information for subsequent review and use. 2.13 System Validation The evaluation phase was conducted upon the completion of the system coding. This phase consisted of verification and validation; interpreted as ensuring the system works as originally designed, and that it meets the requirements stated earlier in this report. Verification is the process of determining how well the system performs in regards to its intended role in actual practice (Moynihan and Singh, 2001). The software had to be tested in a number of different methods: unit tests, module tests, and system test. After the units were verified individually, the modules had to be tested to ensure the capability of the units to link and

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function properly together. Finally, the complete system was verified to insure that all subsystems behaved as expected. The complete system verification was conducted by Drs. Fonseca, Moynihan, and Williamson of The University of Alabama. Validation determines if the system completely and accurately addresses the problem domain, and that it achieves acceptable levels of performance (Moynihan and Singh, 2001). The validation methods selected for this project were predictive and face validation. Several test cases were generated and compared to another expert system designed to assist in the screening of industrial residuals for possible highway construction applications developed by the Institute for Recyclable Materials (IRM) at Louisiana State University. The baseline expert system was validated through the evaluation of test scenarios obtained from the available literature and provided by the same experts from whom the knowledge was gathered (Fonseca et al., 1997). The face validation was conducted with faculty members of the Civil and Environmental Engineering Department at The University of Alabama. Conclusions from the face validation led to enhancements to the developed system’s functionality and recommendations for future versions to include additional capabilities.

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3.0 Use of the System 3.1 Input to System One of the main objectives established in the design phase of the project was to provide the user with a way to easily interface with the computer-based system; this is done via a mouse-driven environment. Additionally, the system was also intended to be straightforward when requesting information to accomplish its analysis. This was accomplished using a forward chaining inference mechanism, which moves in a step by step manner to initially screen the waste for hazardous characteristics, and then identify general and specific road application areas. The first input screen presented to the user is the Initial Screening display which asks the user to enter general data about the waste in question (Figure 3-1). Based on the given inputs, the expert system assesses the ignitability, corrosiveness, and reactivity properties of the residual (Figure 3-2). Based on responses to the initial hazardous characteristics screening, the user may go through the Toxicity Characteristic Leaching Procedure (TCLP) test to determine whether or not the waste is toxic (Figure 3-3).

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After determining the hazardous or non-hazardous nature of the waste, the system starts inquiring about the residual’s chemical and physical properties. Initially, the user must input data on the waste’s oxide compositions (Figure 3-4). Sequential screens require the keying of specific physical properties for the residual to determine general and specific road construction application areas (Figure 3-5 and 3-6). Further analysis may be required to determine more detailed application areas based on a waste characterization test (Figure 3-7).

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The system’s input screens are user friendly. Relevant information regarding technical terms is provided to the user through help menus, hyperlinks, or look-up tables. The source of a waste and associated attributes appear in red color, and their definitions can be accessed by clicking on them. 3.2 System Processing The prototype expert system uses the input given by the user to develop potential civil application areas for the industrial residuals. The system evaluates the waste’s potentially hazardous properties against ignitability, corrosiveness, reactivity, and toxicity levels established by EPA regulations. The system then uses the material’s chemical and physical properties to evaluate if a match exists between the waste’s characteristics and an application in road construction. This comparison is performed through AASHTO test methods. 3.3 Output of the System The main goal of the system’s output interface is to provide all of the necessary information in a clear and easy to understand manner. The output to the user includes a summary of the information input during the analysis. This summary report allows record-keeping and validation. The output report also includes the final conclusion. The potential application areas

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are identified at the bottom of the report for the user to be used as a decision support mechanism (Figure 3-8).

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4.0 Conclusions 4.1 Comments on the Project The developed system serves as the first step to assist the State of Alabama achieve higher payback and benefits from residuals waste recycling. The project represents an effort to develop an automated computer-based system that can effectively evaluate industrial solid waste and their potential use in road construction applications. By taking a knowledge based approach, the system addresses a large number of factors in a structured and logical manner. Also, the developed system was designed in a friendly and efficient Windows environment which allows users with little or no computer training to effectively evaluate material residuals, if the proper technical information is gathered. The benefits of this project are self evident. The foundry industry produces a large amount of waste each year in Alabama. Without proper management, such waste can lead to excessive pollution. The maximum utilization of residuals into public construction operations can have a tremendous impact on the state’s overall economy, on the road construction industry of the state, and on the state’s environmental and recycling program efforts. The system also brings expertise in materials recycling into one consolidated platform, enabling manufacturers to find potential uses for their waste materials without having to possess intimate knowledge on civil engineering applications. In 1978, there were approximately 20,000 landfills in the United States. By 1988, that number had dropped to 5,499. By 2003 the number had been reduced to 3,091. In the U.S., approximately 13 billion tons of non-hazardous waste are generated each year, and most of it originates from industries in raw materials extraction, processing, and manufacturing. Of this 13 billion tons of waste, 6.5 billion tons are produced in manufacturing settings. Although no analysis has been performed to estimate the financial benefits of recycling industrial solid waste, there has been some reported studies done on municipal waste which includes packaging, food scraps, old furniture, yard clippings, bottles, clothes, newspapers, and appliances. Municipal waste only makes up 2% of the total waste stream in the United States. The EPA estimates the total cost of municipal waste disposal to be around $100 per ton. Thus, the total cost of ‘municipal’ waste disposal in the U.S. is around $23.8 billion. This figure does not include the associated financial costs of lost resources, or the costs of landfills and incinerators on public health and the environment. The financial impact to the State of Alabama could be staggering by recycling the non-hazardous solid industrial wastes generated. 4.2 Recommendations for Future Work

1. This project considered only solid waste from foundries, coal fly ash, and reclaimed asphalt pavement. There is a wide range of solid industrial waste in the State of Alabama which needs to be evaluated such as scrap tires, woods products, pulp, paper, and plastic residuals.

2. The development of an expert system under certain conditions, as it was in this case, is very complex. Most of the knowledge encapsulated may be imprecise and uncertain. A fuzzy expert system works by incorporating fuzzy sets and/or fuzzy logic into its

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reasoning process scheme (Kandel,1992). As the knowledge base expands to other industries, the need for fuzzy logic would be reasonable given the domain knowledge of certain recycling applications may not be as standard as that of the foundry industry. The use of fuzzy logic will allow an expert system to generate accurate and concise information even when the domain experts having differing logic during their decision making processes.

3. The open-ended design of the system allows for further versions to include additional functionality. Suggested functionality includes the capability to save and/or e-mail the final report once the analysis is complete, and the addition of hyperlinks to specific EPA guidelines and AASHTO test methods used throughout the system.

4. Future research in the development of a more comprehensive system could involve the addition of physical and mechanical properties which the prototype system does not encompass. By widening the available properties to be analyzed, future versions of the developed system should be able to consider a wider range of potential application areas.

5. Currently, the user must exit the developed system if it is determined the waste being analyzed is hazardous. Future versions of the system may include the ability to analyze potential uses, treatment, or disposal methods for the identified hazardous waste.

6. As the expert system’s functionality expands, a possible area of growth is economic analysis. A module within the system which would allow the user to enter variables such as: volume of waste produced, rate of production, possible transportation methods, equipment required to convert the waste into potential road construction material, etc. These inputs, along with selling prices of the waste, would be used for economic analysis to aid in decision making.

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5.0 References American Association of State Highway and Transportation Officials, Standard specifications for

transportation materials and methods of sampling and testing: part 1, 14th

Ed., AASHTO, Washington, D.C., 1995.

American Society of Civil Engineers, “Solid waste press room”, ASCE, http://www.asce.org/pressroom/publicpolicy/vgwaste.cfm, June 4

th

, 2003. Angeli, C., “An on-line expert system for fault diagnosis in hydraulic systems”, Expert

Systems, Vol. 16, No. 1, pp. 115-120, 1999. Badiru, A., Expert systems applications in engineering and manufacturing, Prentice-Hall,

Inc., Englewood Cliffs, N.J., 1992. Bureau of Mines, Mineral commodity summaries, U.S. Department of the Interior, Washington,

D.C., 1993. Collins, R. and Ciesielski, S., NCHRP synthesis 199: recycling and use of waste materials

and by-products in highway construction, Transportation Research Board, National Research Council, Washington, D.C., 1994.

Environmental Protection Agency, “Electronic code of federal regulations”, EPA, http://ecfr.gpoaccess.gov, March 3, 2004.

Federal Highway Administration and American Coal Ash Association, Fly ash facts for highway engineering, Report No. FHWA-SA-94-081, Washington, D.C., December, 1995.

Federal Highway Administration, “Utilization of recycled materials in Illinois highway construction: reclaimed asphalt pavement”, U.S. DOT, FHWA, http://www.fhwa.dot.gov/pavement/reclpav.htm, January 6, 2004.

Fonseca, D.J., Seals, R.K., Knapp, G.M., and Metcalf, J.B., “Expert system for industrial residuals application assessment”, Journal of Civil Engineering, Vol. 11, No. 3, July, 1997.

Ignizio, J.P., Introduction to expert systems. The development and implementation for rule-based expert systems., McGraw Hill, Inc., New York, N.Y., 1991.

Kandel, Abraham, Fuzzy expert systems, CRC Press, Inc., Boca Raton, FL., 1992. Lester, M., Skumanich, M., and Morgan, J., “A brief summary of pollution prevention software”,

Battelle Seattle Research Centers, September, 1993. Moynihan, G.P., Undemane, A., and Jefcoat, I.A., “Application of expert system technology for

foundry pollution problem”, EDA 2000 Conference, Orlando, FL., pp. 68-73. Moynihan, G.P. and Singh, B., Development of a supplier performance information system,

OSEP Report #662-165, The University of Engineering, College of Engineering, Tuscaloosa, AL., August, 2001.

The Turner-Fairbank Highway Research Center, “Introduction”, TFHRC, http://www.tfhrc.gov/hnr20/recycle/waste, March 3, 2004.

University of Wisconsin-Madison, “Consortium for fly ash use in geotechnical applications”, University of Wisconsin-Madison, http://geoserver.cee.wisc.edu/FAUGA/new_page_1.htm, April 3, 2002.

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6.0 Acknowledgements A special thanks is extended to ALDOT, especially to Ms. Alfedo Acoff, Environmental Coordinator, who aided in the acceptance of the project. The University of Alabama Office of Sponsored Programs and the University Transportation Center for Alabama, especially Dr. Daniel S. Turner, are deeply appreciated for their involvement. A warm thank you is extended to Dr. Derek Williamson and Dr. Andrew Graettinger for their efforts in validating the developed prototype system.