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DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Ground Motion Inputs for the Seismic Shake Table Test

Currently, spent nuclear fuel (SNF) is stored in on-site independent spent-fuel storage installations (ISFSIs) at seventythree (73) nuclear power plants (NPPs) in the US. Because a site for geologic repository for permanent disposal of SNF has not been constructed, the SNF will remain in dry storage significantly longer than planned. During this time, the ISFSIs, and potentially consolidated storage facilities, will experience earthquakes of different magnitudes. The dry storage systems are designed and licensed to withstand large seismic loads. When dry storage systems experience seismic loads, there are little data on the response of SNF assemblies contained within them. The Spent Fuel Waste Disposition (SFWD) program is planning to conduct a full-scale seismic shake table test to close the gap related to the seismic loads on the fuel assemblies in dry storage systems. This test will allow for quantifying the strains and accelerations on surrogate fuel assembly hardware and cladding during earthquakes of different magnitudes and frequency content. The main component of the test unit will be the full-scale NUHOMS 32 PTH2 dry storage canister. The canister will be loaded with three surrogate fuel assemblies and twenty-nine dummy assemblies. Two dry storage configurations will be tested – horizontal and vertical above-ground concrete overpacks. These configurations cover 91% of the current dry storage configurations. The major input into the shake table test are the seismic excitations or the earthquake ground motions – acceleration time histories in two horizontal and one vertical direction that will be applied to the shake table surface during the tests. The shake table surface represents the top of the concrete pad on which a dry storage system is placed. The goal of the ground motion task is to develop the ground motions that would be representative of the range of seismotectonic and other conditions that any site in the Western US (WUS) or Central Eastern US (CEUS) might entail. This task is challenging because of the large number of the ISFSI sites, variety of seismotectonic and site conditions, and effects that soil amplification, soil-structure interaction, and pad flexibility may have on the ground motions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100°C to 300°C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

A HUMAN FACTORS ENGINEERING PROCESS TO SUPPORT HUMAN-SYSTEM INTERFACE DESIGN IN CONTROL ROOM MODERNIZATION

The primary objective of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program is to sustain operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R&D). The Advanced Instrumentation, Information, and Control (II&C) System Technologies pathway conducts targeted R&D to address aging and reliability concerns with legacy instrumentation and control (I&C) and other information systems in existing U.S. NPPs. Control room modernization is an important part following this pathway, and human factors experts at Idaho National Laboratory (INL) have been involved in conducting R&D to support migration of new digital main control room (MCR) technologies from legacy analog and legacy digital I&C. This paper describes a human factors engineering (HFE) process that supports human-system interface (HSI) design in MCR modernization activities, particularly with migration of old digital to new digital I&C. The process described in this work is an expansion from the LWRS Report INL/EXT-16-38576, and is a requirements-driven approach that aligns with NUREG-0711 requirements. The work described builds upon the existing literature by adding more detail around key tasks and decisions to make when transitioning from HSI Design into Verification and Validation (V&V). The overall objective of this process is to inform HSI design and elicit specific, measurable, and achievable human factors criteria for new digital technologies. Upon following this process, utilities should have greater confidence with transitioning from HSI design into V&V.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

A Human Factors Engineering Process to Support Human-System Interface Design in Control Room Modernization

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels - 19294

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100 deg. C to 300 deg. C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Climatology of Aerosol Optical Depth at Mid-Continental US Site: Ground-based Observations

The total aerosol burden in the atmosphere is typically represented by aerosol optical depth (AOD). To capture important and climate-relevant signatures of the aerosol burden, such as year-to-year and seasonal variability, continuous multi-year AOD observations are required. For more than two decades, these observations have been performed at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (CF) using ground-based passive remote sensing. The partially overlapping and fragmentary AOD records at the ARM SGP CF have been provided by four individual instruments, namely two co-located (C1 and E13) Multifilter Rotating Shadowband Radiometers (MFRSRs), a Normal Incidence Multifilter Radiometer (NIMFR), and a Cimel Sunphotometer (CSPHOT). Since these individual records are sporadic with instrument- and time-dependent data quality, development of a continuous multi-year high-quality AOD dataset is a challenging task. In this work, an initial development of a continuous 20-year (1997-2017) high-quality AOD product is introduced. The development involves (1) incorporation of the available data quality information and delivery of the historical time series of AOD with high quality from four individual instruments, (2) comparison of multiple AOD retrievals to identify potential instrument-related issues and/or retrieval problems, and (3) merging these individual time series, generation of a two-decade continuous climatology of high-quality AOD and reporting of the uncertainty estimations of the merged product.

Ground based remote sensing, Atmospheric Radiation↗

DOE OSTI2017

Python and HPC for High Energy Physics Data Analyses

High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectors and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

An introduction to optimal power flow: Theory, formulation, and examples

The set of optimization problems in electric power systems engineering known collectively as Optimal Power Flow (OPF) is one of the most practically important and well-researched subfields of constrained nonlinear optimization. OPF has enjoyed a rich history of research, innovation, and publication since its debut five decades ago. Nevertheless, entry into OPF research is a daunting task for the uninitiated--both due to the sheer volume of literature and because OPF's ubiquity within the electric power systems community has led authors to assume a great deal of prior knowledge that readers unfamiliar with electric power systems may not possess. This article provides an introduction to OPF from an operations research perspective; it describes a complete and concise basis of knowledge for beginning OPF research. The discussion is tailored for the operations researcher who has experience with nonlinear optimization but little knowledge of electrical engineering. Topics covered include power systems modeling, the power flow equations, typical OPF formulations, and common OPF extensions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Exploring the Psychometrics of Common Post-Scenario Human Factors Questionnaires of Workload, Situation Awareness, and Perceived Difficulty

Abstract: The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the primary mission of sustaining operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R&D). In this effort, the role of human factors engineering (HFE) has been an integral in ensuring new digital upgrades that are part of the overall main control room modernization strategy for various U.S. NPPs optimize human-system performance and do not introduce new human failure modes. In this process, testing and evaluation of concept (i.e., prototype) human machine interfaces (HMIs) are done in operator-in-the-loop studies at various stages of the HFE modification process, such as during design and verification and validation (V&V) [1]. During these studies, licensed operators go through select scenarios using a testbed, such as a full-scale simulator or at a NPP’s training simulator, to identify potential usability issues and provide general design feedback regarding the new digital HMIs. Human-system performance is measured and evaluated through a range of objective and self-report measures that capture aspects of plant performance, task performance, workload, situation awareness, and anthropometric and ergonomic concerns [2]. The use of post-scenario questionnaires is an acceptable method for gathering measures of workload and situation awareness. To this end, the NASA-Task Load Index (TLX) [e.g., 3, 4, & 5] and Situation Awareness Rating Technique (SART) [e.g., 6 & 7] are common standardized questionnaires used for evaluating workload and situation awareness, respectively. When combined, these questionnaires consist of a total of 15 questions, each using a different rating scale. Debriefs are also done through interviews with operators to gather design insight after each scenario. Since operator- and training simulator-time is limited, a concern during this post-scenario period of operator-in-the-loop studies is the limited time available to run scenarios, administer post-scenario questionnaires, and debrief within the allotted simulator time. To address this potential problem, this paper explores the psychometric characteristics of NASA-TLX, SART, and a common one-question post-scenario usability questionnaire (i.e., the single ease question – SEQ [8]) in effort to inform future development of a condensed questionnaire that captures aspects of workload and situation awareness. This exploratory work uses data from four different operator-in-the-loop studies completed under prior LWRS operator-in-the-loop studies. Findings from this paper should support future development of a consolidated questionnaire that may be used in operator-in-the-loop studies, when time is compressed, that conforms to the HFE scientific and regulatory requirements set for NPP control room modernization.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

Human factors engineering process to support human-system interface design in control room modernization - 351

The primary objective of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program is to sustain operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R and D). The Advanced Instrumentation, Information, and Control (II and C) System Technologies pathway conducts targeted R and D to address aging and reliability concerns with legacy instrumentation and control (I and C) and other information systems in existing U.S. NPPs. Control room modernization is an important part following this pathway, and human factors experts at Idaho National Laboratory (INL) have been involved in conducting R and D to support migration of new digital main control room (MCR) technologies from legacy analog and legacy digital I and C. This paper describes a human factors engineering (HFE) process that supports human-system interface (HSI) design in MCR modernization activities, particularly with migration of old digital to new digital I and C. The process described in this work is an expansion from the LWRS Report INL/EXT-16-38576, and is a requirements-driven approach that aligns with NUREG-0711 requirements. The work described builds upon the existing literature by adding more detail around key tasks and decisions to make when transitioning from HSI Design into Verification and Validation (V and V). The overall objective of this process is to inform HSI design and elicit specific, measurable, and achievable human factors criteria for new digital technologies. Upon following this process, utilities should have greater confidence with transitioning from HSI design into V and V. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

Bi-objective approaches for home healthcare medical team planning and scheduling problem

In this paper, we study the medical team planning and scheduling in home healthcare within a weekly horizon, including the planning of nursing visits and the daily traveling route scheduling. Two objectives are considered: the first one is to minimize the total operation cost of the healthcare agency and the second one is to maximize the patient satisfaction. The problem is formulated as a mixed integer program, to seek for a trade-off between two objectives, with the characteristics of the patient requirements including nursing types, nursing frequency and service length considered. Medical team types, available service days and overwork penalty are also respected in the model. Then an ϵ-constraint method is adopted to obtain exact non-dominated solutions. To address large-scale problem instances, three heuristic approaches are developed to generate approximate Pareto fronts in a reasonable time. The set of non-dominated solutions are valuable for decision-making. Computational experiments are conducted and the results demonstrate the efficiency of the approaches.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

NDCS Group Meeting Work overview: NCSP Task ORNL IP&D-5 [Slides]

The presentation discusses the primary goal of the NCSP Task IP&D-5 which is to use available data from HPRR operation to create a benchmark report for inclusion in the ICSBEP, as a Criticality Accident Alarm System (CAAS) shielding benchmark. The presentation elaborates on the HPRR operation and how it relates to the KENO VI model, sulfur pellets measurements, and calculation methodology between KENO and MAVRIC FW-CADIS. The presentation concludes by stating that some work is still needed to evaluate uncertainties and to explain the discrepancy computation/experiment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

User Guide to the Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software (V.1.0)

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the initial software release as ADDER v1.0.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

User Guide to the Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software (V.1.01)

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.0.1. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

FUSRAP Case Study - Benefits and Lessons Learned from Implementation of a Modern Data Solution at Maywood - 18399

This paper focuses on data production and management practices dating back to 1999 that continue to evolve to support the project today. In 2000, the FUSRAP Maywood Project began using a software environmental data management system and laboratory information management system, developed by a single database administrator (DA) and authored in Microsoft Access{sup TM} (MS Access). The original databases included basic functionality including sample number assignment and label generation, tracking of LIMS gamma spec QC and assignment of basic qualifiers and basic database queries. The DA continued over the next fifteen years to refine the EDMS/LIMS by integrating project-specific data evaluation guidance document processes and Quality Assurance/Quality Control (QA/QC) charting and excursion warning tools. With the retirement of the original DA, the U.S. Army Corps of Engineers (USACE)-Cabrera Team procured and implemented a commercial-leaning solution using modern database tools and an established EDMS vendor. For the database transition process, the project team established and configured the new EDMS/LIMS with basic architecture and accessibility; evaluated existing workflows; established/revised LIMS and EDMS-related documentation (manuals and procedures); and conducted dry runs and validation testing. The overall team coordinated closely to facilitate a seamless transition from initial assessment and authoring, to data migration, and finally to resumption of normal ongoing operations. Key features of the new EDMS Subcontractor's software included lookup tables, an import wizard, data checking options and unique indexes. Since the database systems became operational, the technical staff gathered useful feedback from end users (e.g., lab staff, field engineers, task managers, and the third-party data validator) to refine the EDMS/LIMS operation. This feedback triggered improvements in the performance of onsite laboratory qualification forms, promoted consistency in sample ID numbers between the database sample planning screens and field chain-of-custodies, corrected bugs in the LIMS Duplicate Evaluation Report, eliminated data import issues such as blank, inconsistent or missing data from key fields. One of the advantages of the commercial database solution was that it allowed the project to cut cost over time due to the lower cost of database maintenance provided by the commercial database vendor versus the cost of an on-staff DA. Cost savings are estimated at $40,000 per year. There were also indirect cost savings resulting from implementation of the new database since it allowed better integration of the LIMS and EDMS. While there will always be challenges associated with long term records/data management for any old remediation site, the Maywood Team's approach to an upgraded EDMS/LIMS implementation serves as one element of the overall effort to enhance the integrity and reproducibility of critical data that supports the remediation program while at the same time, more effectively using available resources. These lessons-learned will enhance implementation of cost-effective solutions for similar environmental remediation sites. (authors)

97 MATHEMATICS AND COMPUTING↗