Results for “knowledge base” — Page 7

DOE OSTI2021

Software-defined Networking for Energy Delivery Systems (SDN4EDS): An Architectural Blueprint (Final Report)

This is the initial version of a reference for suppliers and energy companies of all sizes to deploy networks based on software-defined networking technology (SDN) to improve reliability, reduce cyber security attack surface, and facilitate mitigation of adversarial behavior. It is a living document and will progress over the life cycle of the Software-Defined Networking for Energy Delivery Systems (SDN4EDS) project. Version 2 of this report provides information on the Red Team tabletop assessment performed against the initial reference architecture. Version 3 of this report updates the reference architecture with lessons learned from the Red Team tabletop assessment, as well as provides additional details for the use cases. It also provides information on the decision process that could be used by an organization when considering deploying SDN in their environment. The final version of this report consolidates all the interim reports generated by the project into a final report. It also draws from PNNL’s experience in deploying SDN to make recommendations on how SDN could be deployed in a utility environment, and provides rationale for those decisions allowing individual utilities to make risk-based and knowledge-based decisions on how to best deploy SDN in their own environment

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Software-defined Networking for Energy Delivery Systems (SDN4EDS): An Architectural Blueprint (Final Summary Report)

This is the initial version of a reference for suppliers and energy companies of all sizes to deploy networks based on software-defined networking technology (SDN) to improve reliability, reduce cyber security attack surface, and facilitate mitigation of adversarial behavior. It is a living document and will progress over the life cycle of the Software-Defined Networking for Energy Delivery Systems (SDN4EDS) project. Version 2 of this report provides information on the Red Team tabletop assessment performed against the initial reference architecture. Version 3 of this report updates the reference architecture with lessons learned from the Red Team tabletop assessment, as well as provides additional details for the use cases. It also provides information on the decision process that could be used by an organization when considering deploying SDN in their environment. The final version of this report consolidates all the interim reports generated by the project into a final report. It also draws from PNNL’s experience in deploying SDN to make recommendations on how SDN could be deployed in a utility environment, and provides rationale for those decisions allowing individual utilities to make risk-based and knowledge-based decisions on how to best deploy SDN in their own environment. This summary report provides a higher-level overview of the project reports. Readers interested in additional detail, including results of the Red Team assessments and the final configuration, are encouraged to read the full final report.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-02: Setting the Stage for Incorporation of Toxicity Measures in Treatment Plan Assessments

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-CD-209-09: Quickly Identifying Good Candidates for Proton Therapy From Geometric Considerations

Purpose: We developed a knowledge-based model that can predict the patient-specific benefits of proton therapy based upon geometric considerations. The model could also aid patient selection in model-based clinical trials or help justify clinical decisions to insurance companies. Methods: The knowledge-based method trains a model upon existing proton treatment plans, exploiting correlations between dose and distance-to-target. Each OAR is split into concentric subvolumes surrounding the target volume, and a skew-normal PDF is fit to the dose distribution found within each shell. The model learns from shared trends in how the best-fit skew-normal parameters depend upon distance-to-target. It can then predict feasible OAR DVHs for a new patient (without a proton plan) based upon their geometry. The expected benefits of proton therapy are assessed by comparing the predicted DVHs to those of an IMRT plan, using a metric such as the equivalent uniform dose (EUD). Results: A model was trained for clival chordoma, owing to its geometric complexity and the multitude of nearby OARs. The model was trained using 20 patients and validated with a further 20 patients, and considers several different OARs. The predicted EUD was in good agreement with that of the actual proton plan. The coefficient of determination (R-squared) was 85% overall, 92% for cochleas, 80% for optic chiasm and 79% for spinal cord. The model exhibited no signs of bias or overfitting. When compared to an IMRT plan, the model could classify whether a patient will experience a gain or a loss with an accuracy between 75% and 95%, depending upon the OAR. Conclusion: We developed a model that can quickly and accurately predict the patient-specific benefits of proton therapy in clival chordoma patients, though models could be trained for other tumor sites. This work is funded by National Cancer Institute grant U19 CA 021239.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Insights and Trends from a Literature Assessment of the Thorium Fuel Cycle

The thorium fuel cycle is often perceived to have limited experience, thereby imposing a barrier to its implementation. Thorium fuel cycles do not have the degree of commercial-scale experience associated with the uranium fuel cycle (especially the use of uranium oxide in a once-through configuration in light- or heavy-water reactors); however the abundance of major research campaigns - and the test and demonstration reactor operations that capped these campaigns - illustrate that significant knowledge concerning the use of thorium is available. Part of the reason for thorium's perceived immaturity is that the information is scattered among a multitude of sources and has not previously been consolidated and evaluated on a comprehensive scale. In recognition of this challenge, Vanderbilt University (VU) and Oak Ridge National Laboratory (ORNL) included a thorium fuel cycle literature assessment task as part of their Nuclear Energy University Programs (NEUP) project. The first phase of this literature assessment culminated in a comprehensive report. This paper describes the highlights of the initial version of this literature report, including item quantification, trends by category, and implications. This preliminary literature assessment has identified that a wealth of documented experience with thorium fuel cycles exists, across many varieties and specific technology options. Though a significant share of the literature is comprised of systems studies and/or proposed work, there is also a substantial knowledge base from experimentation and demonstration with thorium fuel cycle technologies. It is intended that this initial literature report serve as a starting point for continued discussions and consolidation of thorium fuel cycle literature. There are likely still records of work from the 1950's to the 1970's (and even more recently) which could be significant but were not adequately catalogued or are not readily available to a broad audience; hopefully, the ongoing discussions that have been spurred by the present work will stimulate making these documents available. The authors strongly encourage those with knowledge of additional data sources to share them with the interested community. Furthermore, the 21. century is experiencing a resurgence in thorium fuel cycle work that continues to develop the knowledge base. Thus, it would be beneficial to produce updated accounts of this thorium literature summary in future years. Ultimately, the items identified during the course of this literature assessment, along with additional items that continue to be identified, will be housed in an information repository. This will take the form of a relational database, with specific functionality to be determined based on user interest. This format is intended to enable future users to quickly find specific topics or sources as well as assess how much information is available about a particular topic. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Use of generic and site-specific underground research laboratories to support siting, design, and safety assessment - 15417

Under the auspices of the International Atomic Energy Agency (IAEA), nationally developed underground research laboratories (URLs) and associated research institutions are being offered for use by other nations. These facilities form an Underground Research Facilities (URF) Network for training in and demonstration of waste disposal technologies and the sharing of knowledge and experience related to geologic repository development, research, and engineering. In order to achieve its objectives, the URF Network regularly sponsors workshops and training events related to the knowledge base that is transferable between existing URL programs and to nations with an interest in developing a new URL. Toward that end, a three-day workshop was held in Albuquerque, New Mexico in October 2014 to identify and compare the understanding of URF Network members on the place and role of generic and site-specific URLs in the overall, iterative geological disposal development process, including repository siting, design, and post-closure safety assessment. Attention was also given to the need for URLs in salt host rock, since there is currently no such facility in operation in the world. This paper describes some of the outcomes of the workshop in the context of the general timeline for repository development and the evolving role of research, development, and demonstration (RD and D) activities in URLs. Of particular interest is the relationship between technology maturity, as measured by technology readiness level (TRL), and the stages or milestones in the repository development timeline. The long history of RD and D in worldwide URLs (> 40 years) can be argued to be the primary reason that nuclear waste disposal systems are currently at a high level of maturity. One of the key recommendations from the workshop was that an international, easily accessible knowledge base should soon be established to avoid the loss of important experiences and information obtained from existing and closed URLs. It was also recognized that a new generic URL in salt host rock would provide a number of benefits, but one should not be initiated until a national program specifically decides to site its repository in salt. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Nucleation and Crystal Growth in the Formation of Hierarchical Three-Dimensional Nanoarchitecture

This project is to obtain fundamental understandings of the operation of the Ostwald-Lussac (OL) Law and the oriented attachment (OA) mechanism in nucleation and growth of TiO2 nanorods (NR) via surface-reaction-limited pulsed chemical vapor deposition (SPCVD) process. Three-dimensional (3D) NW networks are a unique type of mesoporous architecture that offers extraordinary surface area density and superior transport properties of electrons, photons, and phonons. It is exceptionally promising for advancing the design and application of functional materials for photovoltaic devices, catalysts beds, hydrogen storage systems, sensors, and battery electrodes. Our group has developed the SPCVD technique by mimicking the mechanism of atomic layer deposition (ALD), which effectively decoupled the crystal growth from precursor concentration while retaining anisotropic 1D growth. For the first time, this technique realized a 3D NW architecture with ultrahigh density and achieved ~4-5 times enhancement on photo-conversion efficiency. Through the support of our current DOE award, we revealed the governing role of the OL Law in the nucleation stage of SPCVD. The formation of NR morphology in SPCVD was identified following the OA mechanism. We also discovered a unique vapor-phase Kirkendall effect in the evolution of tubular or core-shell NR structures. These understandings opened many new opportunities in designing 3D NW architectures with improved properties or new functionalities. Specifically, our accomplishments from this project include five aspects: (1) Observation of the Ostwald-Lussac Law in high-temperature ALD. (2) Observation of vapor-solid Kirkendall effect in ZnO-to-TiO2 nanostructure conversion. (3) Development of highly-efficient capillary photoelectrochemical (PEC) solar-fuel generation. (4) Development of efficient and stable electrochemical protections for black silicon PEC electrodes. (5) Development of doped polymers with tunable electrical properties. This project brings a new level of transformative knowledge on nucleation and crystal growth in the SPCVD NR growth processes. Specifically, quantification of the activation energy landscape guided by the OL law will allow us to establish a critical knowledge base of nucleation kinetics for SPCVD synthesis of NR branches on different material surfaces. Studying the OA kinetics will establish a transformative knowledge base to support this new crystal growth mechanism that can be applied to many functional material systems. This research will pave the road toward a capable and versatile synthesis technology for creating 3D hierarchical mesoscale structures.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enhancing Knowledge Capture and Management within a Knowledge-Driven Workforce [Capstone Project]

This project aimed to understand how the collective knowledge of a group of engineers or ‘knowledge-based workers’ can be baselined through use of qualitative questionnaires based on input from subject matter experts. The results of the questionnaires were then used to inform management and the group where to focus efforts on terms of training and mentoring. With use of re-administering the qualitative questionnaire to gauge progress over time. Additionally, the development a knowledge-based wiki was explored to help shape group culture from one where ideas and knowledge tend to be siloed, into one where information is traded freely across the group and with external customers and collaborators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Harmonizing model organism data in the Alliance of Genome Resources

The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein–protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Development Impact Assessment Highlights Co-benefits of GHG Mitigation Actions

This EC-LEDS document describes the Development Impact Assessment (DIA) process that explores interactions between development goals and the low emission development strategies. DIA aims to support informed decision-making by considering how policies and programs intended to meet one goal may impact other development priorities. Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) is a flagship U.S. government-led effort that assists countries in developing and implementing LEDS. The program enhances partner country efforts by providing targeting technical assistance and building a shared global knowledge base on LEDS. is a flagship U.S. government-led effort that assists countries in developing and implementing LEDS. The program enhances partner country efforts by providing targeting technical assistance and building a shared global knowledge base on LEDS.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Radiation Damage In Reactor Cavity Concrete

License renewal up to 60 years and the possibility of subsequent license renewal to 80 years has established a renewed focus on long-term aging of nuclear generating stations materials, and recently, on concrete. Large irreplaceable sections of most nuclear generating stations include concrete. The Expanded Materials Degradation Analysis (EMDA), jointly performed by the Department of Energy, the Nuclear Regulatory Commission and Industry, identified the urgent need to develop a consistent knowledge base on irradiation effects in concrete. Much of the historical mechanical performance data of irradiated concrete does not accurately reflect typical radiation conditions in NPPs or conditions out to 60 or 80 years of radiation exposure. To address these potential gaps in the knowledge base, The Electric Power Research Institute and Oak Ridge National Laboratory are working to disposition radiation damage as a degradation mechanism. This paper outlines the research program within this pathway including: (i) defining the upper bound of the neutron and gamma dose levels expected in the biological shield concrete for extended operation (80 years of operation and beyond), (ii) determining the effects of neutron and gamma irradiation as well as extended time at temperature on concrete, (iii) evaluating opportunities to irradiate prototypical concrete under accelerated neutron and gamma dose levels to establish a conservative bound and share data obtained from different flux, temperature, and fluence levels, (iv) evaluating opportunities to harvest and test irradiated concrete from international NPPs, (v) developing cooperative test programs to improve confidence in the results from the various concretes and research reactors, (vi) furthering the understanding of the effects of radiation on concrete (see companion paper) and (vii) establishing an international collaborative research and information exchange effort to leverage capabilities and knowledge.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Comparative evaluation and selection of heat exchangers using multicriteria decision-making

Here, this study presents a well-structured method for comparing and selecting Heat Exchanger (HE) technologies for Integrated Energy Systems (IES). The decision to select a HE for a particular IES configuration can vary greatly depending not only on engineering requirements but also on customer’s specific demand. In other words, the HE selection for IES requires a multicriteria decision-making approach, taking into account diverse technical, economic, and safety aspects, as well as the relative priorities considered by energy users. This study employs a HE evaluation approach combining multicriteria decision-making techniques widely used in various industries: quality function deployment (QFD) and analytic hierarchy process (AHP) techniques. Of particular interest is the use of the proposed method to select a high-temperature HEs that couples advanced nuclear reactors and industrial processes. To build a practical basis for comparing HEs within the proposed framework, efforts were made to identify the various HEs requirements for IES purposes. In addition, leveraging the insights obtained from the literature review and the market survey of commercial HE suppliers, a knowledge base was built to facilitate the comparison of each requirement across various HE designs. Also, evaluation metrics were identified for HE requirements with robust rational to enhance the quality of decisions made throughout the proposed evaluation process. The evaluation procedure and knowledge base described in this study can provide a useful basis for those interested in screening the appropriate HE designs for various IES scenarios.

Analytic Hierarchy Process (AHP)↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2012

D and D Knowledge Management Information Tool - 2012 - 12106

Deactivation and decommissioning (D and D) work is a high priority activity across the Department of Energy (DOE) complex. Subject matter specialists (SMS) associated with the different ALARA (As-Low-As-Reasonably-Achievable) Centers, DOE sites, Energy Facility Contractors Group (EFCOG) and the D and D community have gained extensive knowledge and experience over the years in the cleanup of the legacy waste from the Manhattan Project. To prevent the D and D knowledge and expertise from being lost over time from the evolving and aging workforce, DOE and the Applied Research Center (ARC) at Florida International University (FIU) proposed to capture and maintain this valuable information in a universally available and easily usable system. D and D KM-IT provides single point access to all D and D related activities through its knowledge base. It is a community driven system. D and D KM-IT makes D and D knowledge available to the people who need it at the time they need it and in a readily usable format. It uses the World Wide Web as the primary source for content in addition to information collected from subject matter specialists and the D and D community. It brings information in real time through web based custom search processes and its dynamic knowledge repository. Future developments include developing a document library, providing D and D information access on mobile devices for the Technology module and Hotline, and coordinating multiple subject matter specialists to support the Hotline. The goal is to deploy a high-end sophisticated and secured system to serve as a single large knowledge base for all the D and D activities. The system consolidates a large amount of information available on the web and presents it to users in the simplest way possible. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

At the Core: Fundamental Building Science Education Matters More Than Building Type

As building technologies become more advanced, the need for highly skilled and qualified workers has increased. Both residential and commercial building industries struggle to capture the full benefit of these new technologies because of the limited building science knowledge base of the professionals researching, designing, building, and selling these structures. To help address this need, the U.S. Department of Energy’s (DOE’s) Residential Building Integration (RBI) program initiated the Guidelines for Building Science Education (GBSEs). These guidelines provide guidance on the fundamental building science knowledge base that is helpful for a wide range of building industry jobs. This effort provides a mechanism for training organizations to align core curriculum that can be applied to any building type. At the same time, DOE’s Commercial Building Integration (CBI) program has been spearheading a full suite of impactful initiatives including the Better Buildings Workforce Guidelines (BBWGs), which provide voluntary national guidelines from which select stakeholders can develop high-quality and nationally recognized training and certification programs. The BBWG framework helps to improve quality and scalability issues for five energy efficiency-related jobs: Building Energy Auditor, Building Commissioning Professional, Building Operations Professional, Building Operations Journey-Worker and Energy Manager. The residential and commercial building programs are both interested in helping to create better buildings through an improved workforce. The two program initiatives complement each other in many ways. The GBSEs pave the way for more specialized training and education offered by industry and academia, which lead to credentials that signify competency. The BBWGs cover credentialing for energy efficiency jobs—a critical area that DOE believed could benefit from incentives for credentialing bodies and building operators that would improve the energy efficiency of commercial buildings. This paper summarizes the steps DOE programs have taken to work together and the outcome of this symbiotic relationship.

Metzger, Cheryn E.↗