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NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

Safety in Artificial Intelligence: Challenges and Opportunities for the U.S. National Labs and Beyond

This report discusses the importance of the critical and underexplored topic of artificial intelligence (AI) safety, as highlighted during the “Strategy Alignment on AI Safety” workshop convened at Lawrence Livermore National Laboratory (LLNL) in April 2024. Through a summary of keynote talks, panel discussions, and breakout sessions, world-leading AI safety experts from academic, industry, national labs, and government agencies clearly agree on the need for and importance of large-scale investments for research and capabilities in AI safety. With the field innovating at unprecedented rates, there is increasing urgency to develop novel evaluation methodologies that allow full considerations of risks/threats of AI technologies in different domains. Quantitative metrics and effective methodologies that can evaluate and audit the “safeness” of how a given AI technology is trained, deployed, or regulated are, at best, nascent for certain scenarios or, more commonly, nonexistent. This maturation gap presents the possibility of serious threats to national security, and further inaction may have serious consequences. Additionally, the gap between the public’s and research community’s perceptions of AI risks/rewards is significant. While numerous voices from the AI community have expressed concern that the risks could be so high that future AI systems could inflict extinction-level damage to humanity if deployed incorrectly, the public largely is aware only of risk in low-impact scenarios. This discrepancy highlights the crucial need for researchers to articulate to governmental bodies what, why, and when various AI risks matter as part of motivating funding requests. Thus, the call to action for this community is to pursue AI safety as a “Big Science” project on a scale comparable to the Manhattan Project. High risks and high payoffs are on the table, but safe AI is a fast-moving target, and large-scale investments are needed to guide development of this technology in a responsible way. We highlight the need for a multilayered solution combining the development of new methods and algorithmic approaches to mitigate threats with an active participation of the government(s) in setting high industry standards and regulations based on state-of-the-art technology. The U.S. Department of Energy (DOE) national laboratories have served as leading institutions for scientific innovation in the U.S. for more than 70 years. Drawing on their expertise in the AI community and their history of safeguarding critical and sensitive information, and as we look to the future, national labs are the best choice for evaluating and safeguarding AI technologies.

97 MATHEMATICS AND COMPUTING↗

MRM Evaluation Research Program

This is an interim report on the current output of the MRM evaluation research program. During 1998 this research program has used new and existing data to create an important tool for the development and improvement of "maintenance resource management" (MRM). Thousands of surveys completed by participants in airline MRM training and/or behavior change programs have, for the first time, been consolidated into a panel of "MRM Attitudes and Opinion Profiles." These profiles can be used to compare the attitudes about decision making and communication in any given company at any stage in its MRM program with attitudes of a large sample of like employees during a similar period in their MRM involvement. This panel of comparison profiles for attitudes and opinions is a tool to help audit the effectiveness of a maintenance human factors program. The profile panel is the first of several tools envisioned for applying the information accumulating in MRM databases produced as one of the program's long range objectives.

Taylor, James C.↗

Use of Historical EM Practices and Policies for Management of Cleanup Program and Address GAO Concerns - 20222

As Department of Energy (DOE) Environmental Management (EM) program policies and management practices are revised over time, it might be useful to periodically reflect on the DOE EM program's past to identify practices that have worked and those that might be appropriate for possible reuse in the future. An added impetus to examine alternative approaches is the recent Government Accountability Office (GAO) report entitled 'Nuclear Waste Cleanup - DOE Could Improve Program and Project Management by Better Classifying Work and Following Leading Practices.' The February 2019 GAO report states that EM categorizes most of its work in a way that does not adequately involve independent experts and DOE senior leadership. It also noted that EM has not followed leading practices for program and project management that could help keep the cleanup efforts on schedule and control costs. The GAO report recommended that EM, working with DOE Office of Project Management (PM): - Establish requirements and then assess EM's ongoing operations activities to determine if some activities should be reclassified as capital asset projects based on these newly established requirements. - Review and revise EM's 2017 cleanup policy to include program management leading practices related to scope, cost, schedule performance, and independent reviews. - Update the cleanup policy to require that earned value management (EVM) systems be maintained and used in a way that follows EVM best practices. - Develop a policy to ensure that work is categorized as level of effort (LOE) only in appropriate, specified circumstances, such as when work is not measurable or when measurement is impractical. - Integrate EVM data into EM's performance metrics for operations activities. To assist with improving program performance and implementing audit recommendations, this paper reviewed past successful cleanups such as Weldon Springs, Rocky Flats, Fernald, Ashtabula, Battelle Columbus (abs, and other historical resources and people with experience during the early years of EM program. As such, there are several past practices which may well be suited for reuse today. Some of these practices include: - In 1990's, as the DOE EM cleanup program, known as Environmental Restoration came into effect, the known cleanup scope at each geographic location or site was organized into four levels ranging from overall site-wide cleanup effort to the individual 'release sites', providing high granularity to the program. - The cleanup program was organized by geography (Northwest, Southwest, Eastern Area Programs, etc.). These 'sub-program' managers provided a degree of Headquarters oversight and management allowing upper management (EM-1, 2, and 3) to focus on major decisions and issues. - Budget levels at selected cleanup sites were funded above 'minimum-safety' levels to accelerate actual cleanup work. - Past practice utilized EVM techniques and uniform EM oversight over all discrete project-like activities, providing for a coordinated cleanup effort. - EM managed LOE activities using benchmarking and best in class management practice techniques to help manage costs. - EM managed and reviewed entire site cleanup baselines, not only individual projects, focusing on a successful overall outcome. - Sites had a 'Road map' or 'Management Action Plan' that provided the overall strategy or plan for that site's cleanup - this helped with understanding and coordination of efforts. - EM had a robust lessons-learned program and database to capture and transmit worthy ideas. - EM had well-structured cleanup baseline change control policies to control cost and schedule changes, at the contractor and higher Headquarters levels. Finally, some of the GAO observations may be valid, however it is not clear as to their extent. For example, for some operation types of work, the use of the Level of Effort (LOE) earned value method to track progress may be appropriate. Also, to ensure independence of thought, and to obtain useful insight on past practices, it may be suitable to have former EM employees to assist with understanding past practices or to verify that activities have been properly identified. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Establishing a Technical Assistance Network to Build Capacity in Southwest Alaska (Southwest Alaska Energy Network - Final Report)

The Southwest Alaska Municipal Conference (SWAMC) is a non-profit regional membership economic development organization that represents the Aleutian/Pribilof Islands, Bristol Bay, and Kodiak regions of southwest Alaska. SWAMC applied for the DOE-OIE Establishment of an Inter-Tribal Technical Assistance Energy Providers Network grant FOA to work with our partners to provide energy planning and project development technical assistance. The project team was made up of SWAMC, three regional organizations, a management consulting firm, and a panel of technical consultants. SWAMC sub-contracted with the three Alaska Native regional non-profit organizations – Aleutian Pribilof Islands Association (APIA), Bristol Bay Native Association (BBNA), and Kodiak Area Native Association (KANA) – to fund full or partial Regional Energy Coordinator (REC) positions. The project period ran from September 2016 to March 2020. The project goal was to help southwest Alaska regional tribal partners and communities to develop efficient and financially sustainable structures for identifying and developing energy projects that enhance community resiliency and energy sustainability. This project established energy coordinators and management structures in the Aleutian, Bristol Bay, and Kodiak regions to expand technical assistance capacity of regional residents; demonstrate this capacity by advancing energy efficiency, heat, and power supply projects; and secure long-term funding commitments to establish a sustained technical assistance structure. The project team expanded technical assistance capacity of energy coordinators and regional stakeholders in several ways: by providing funding for the SWAMC project manager to attend three Office of Indian Energy trainings; for energy coordinators to attend numerous energy conferences; for utility clerks from several villages to receive one-on-one reporting training on Alaska’s Power Cost Equalization electric subsidy program; and for the Kodiak REC to complete the Arctic Remote Energy Networks Academy and NREL’s Executive Energy Leadership Academy. The energy coordinators demonstrated and shared their increased capacity by hosting several public events: SWAMC hosted two full-day energy workshops in February 2017 and 2018; the Kodiak REC hosted seven Energy Committee meetings for Kodiak stakeholders and gave several presentations at other events; and SWAMC and BBNA organized a Bristol Bay Regional Energy Visioning Session in May 2019. The project team created platforms to both share and request information to involve energy stakeholders in this project, including an energy website, a Facebook group, a periodic newsletter, surveys, mass emails, and paper mailers. An increase in regional capacity was demonstrated through several grant awards, including a $1.2 million USDA grant for Akhiok for an electric distribution infrastructure replacement; an AHFC Kickstarter grant for Aleknagik to audit 2 Tribal and 3 City buildings; and installation of an Air Source Heat Pump demonstration project in Atka. Two communities and one region – Ouzinkie (May 2017), Ugashik (July 2017), and the Bristol Bay region (May 2019) – utilized DOE’s technical assistance services to hold Strategic Energy Planning sessions with NREL and DOE facilitation assistance. And in early 2018, SWAMC established a parallel program, funded through a USDA Energy Audit and Renewable Energy Development grant to provide subsidized energy audits for small businesses in the region. SWAMC and partners have now completed energy audits of over 60 businesses (buildings and fishing vessels) and are currently operating a third round of the USDA program. Fifteen of those business owners have now received additional grant funding to cover 25% of the cost of the energy efficiency upgrades identified in the audit. This technical assistance structure will be sustained beyond DOE grant funding in several forms. As a sign of increased grant writing and project management capacity, the Kodiak Regional Energy Coordinator applied for and received a USDA Community Facilities Technical Assistance and Training grant to continue work begun under this program. Energy coordination tasks have been folded into existing economic development positions at SWAMC and at BBNA, ensuring long-term outreach and support in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A System Approach to Deep Heating Savings Through Measurement, Management, and Motivation

Across multi-tenant commercial office and multifamily buildings, centrally metered fuel use represents a substantial fraction of whole-building energy use. Energy audit practitioners understand that improving heating distribution efficiency is typically more of an opportunity than combustion efficiency and that differing thermal comfort preferences between tenants are the bane of operators across these building typologies. There is an unmet market need for retrofit technologies that allow for the delivery of the right amount of heat to the right spaces, at the right time. The Energy Management and Information System (EMIS) package fills this gap through enhanced controls and metering, incorporating low-cost sensors and wireless communication infrastructure to provide a platform for ongoing commissioning and tenant feedback, including heat cost allocation. With support from the US DOE Building Technologies Office, Steven Winter Associates, Inc. (SWA) partnered with Sentient Buildings, E Source, building owners, and utility and policy stakeholders, to demonstrate a market viable EMIS that achieves a reduction in space heating energy use by reducing heating load, improving control, and positively impacting behavior while providing an acceptable financial return. In this study, EMIS packages were implemented in two New York City multifamily rental buildings. Both buildings conducted basic mechanical work (e.g., repairing steam traps) to ensure the heating system was operating well before any tenant feedback was layered in. Heating Energy Use Reports (HEUR) were created to provide tenants with social comparisons and energy savings tips to influence their behavior; these were provided monthly to all tenants in both buildings. Additionally, one building allocated heating costs to a portion of the tenants. Heat cost allocation (HCA) has a long history in the European Union (EU), although it is not common in the US or in steam-heated buildings. SWA leveraged existing EU best practices and stakeholder feedback to develop a Heat Cost Allocation algorithm that was considered equitable and intuitive. Energy use and tenant behavior impacts were tracked throughout the study. The basic mechanical repair work saved between 11-20% of heating energy. Those savings rose to 17-24% with the addition of tenant feedback. While it may not be possible to precisely determine the impact of COVID-19 on research studies like this, there may have been additional savings realized had the study taken place in a period of normal occupancy patterns. These types of central heating systems have been a blind spot for utilities, who have traditionally had little visibility into detailed behind-the-meter gas usage. Heating energy savings stayed consistent during the coldest months, indicating the potential for utilities to utilize EMIS packages for peak gas demand reductions or demand response programs. Tenant comfort was also improved. Post installation, room temperatures more closely matched thermostat set points. Perhaps due to this greater level of control, the vast majority of tenants being billed for heating were accepting of the allocation costs. And tenants receiving heat cost allocations were more likely to reduce their thermostat setpoints than tenants receiving behavioral feedback without financial impacts were. Variation in building specifics makes it difficult to provide precise energy and financial savings estimates. But within the range of expected conditions, the study identified a few key variables that can have the greatest impact on financial returns: the cost of fuel, the ability and willingness to allocate heating costs to tenants, and a well-functioning heating system as a starting point. This study focused on two multifamily buildings, but additional use cases, such as commercial buildings and affordable housing, should be explored to better understand the full market potential. While this type of upgrade has the potential for deep energy reductions and cost savings, future projects should take into account the balance of costs and benefits between owners and tenants, especially in the affordable, regulated, or other low-to-moderate income (LMI) segments of the market. Rent credits, utility allowances, or a shared savings program are possible options to accelerate adoption of this strategy in these market segments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Management Information Systems Technical Resources Report

Guide supports federal facility staff in understanding, designing, procuring, and implementing Energy Management Information Systems (EMIS) as a valuable component of their portfolio-level energy and water planning and management strategies. As a broad and rapidly evolving family of tools that monitor, analyze, and control building energy use and system performance, EMIS tools present significant opportunities for federal sector energy savings and improved operational performance. EMIS are at the forefront of transforming energy management best practices by providing building owners and operators with well-organized building performance and energy consumption data, enabling a host of analytic capabilities. These capabilities include portfolio-wide energy benchmarking, data visualization, and key performance indicator tracking; automated fault detection and diagnostics (AFDD); artificial intelligence for predictive analytics and control; automated measurement and verification of energy conservation measures; and supervisory control enabling automated system optimization and demand management.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bay Area Regional Energy: Network Integrated Commercial Retrofits (BRICR) Project. Final Report

The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mitigating Algorithmic Bias in Cancer Site Classification Models

Purpose Integrating artificial intelligence in cancer diagnostics has improved tumor classification beyond rule-based systems. Despite these advancements, these models may still encode demographic biases. We conducted a large-scale, applied bias-probing study of a deep learning–based cancer site classifier to quantify race information encoded in document embeddings. We then evaluated how performance changes when race-correlated embedding dimensions are removed in a post-training sensitivity analysis. Methods The cancer site classifier was trained using 3.5 million electronic cancer pathology reports from six of the National Cancer Institute's SEER registries. We trained a hierarchical self-attention network to generate 400-dimensional document embeddings. These embeddings were used to train two downstream, gradient-boosted decision tree classifiers: one to classify the cancer sites and another to predict racial categories. We identified overlapping features by intersecting the top 50 feature-importance rankings from the site and race models and computed their cumulative feature importance in each model. As a post hoc sensitivity analysis, we progressively pruned these overlapping dimensions, retrained the site model, and compared overall macro-F1 and accuracy, race-stratified macro-F1, and group fairness metrics on the basis of demographic parity and equalized odds before and after pruning. Results The analysis revealed minimal feature overlap between the cancer site and race prediction models, and the cumulative importance scores indicated a negligible influence of racial information on clinical predictions. Post-training pruning of overlapping features did not compromise the models' diagnostic accuracy, with a 0.07% loss in accuracy. Conclusion Our findings demonstrate that HiSAN-generated embeddings from SEER data can be used effectively in cancer site classification without significant demographic bias influencing the outcomes. Post-training pruning therefore functions as a practical audit and sensitivity check.

Shivanna, Abhishek [ORNL] (ORCID:0009000665228593)↗

Incentivizing Cold-Climate Efficiency in Juneau (Final Report)

This is the final technical report for the DOE EERE BTO project Incentivizing Cold-Climate Efficiency in Juneau. The project implemented a community energy campaign to deploy heat pumps and efficiency for residents of Juneau, in Southeast Alaska. The project helped Juneau make progress towards its renewable energy goal of reaching 80% renewable energy for space heating by 2045. The Incentivizing Cold-Climate Efficiency in Juneau (ICE-Juneau) project began in 2020 and concluded three years later in 2023. During that time, a group of implementation partners and a research advisory team instituted a beneficial electrification campaign to promote energy savings and carbon reduction in residences of Juneau, Alaska. The campaign, Thermalize Juneau, focused on the installation of single head ductless mini-split heat pumps along with other efficiency upgrades. Thermalize Juneau was the first campaign of its kind in Alaska. After several months of planning, registration opened to the public in early 2021, and over the course of six months 164 participants enrolled. Campaign staff provided education to homeowners on heat pumps and efficiency, and each participant received a one-on-one heat pump assessment using a custom Microsoft Excel-based calculator that estimated energy savings for their residence based on building characteristics and past utility bills. Participants could also obtain a free energy audit from one of the two local energy auditors to further inform their decision. A heat pump installer, electrician, and builder were selected via a competitive RFP process. Participants who felt ready to install a heat pump or other efficiency upgrades received a site visit and custom quote from each of these contractors free of charge, and if they still felt energy upgrades were right for them, could move forward with an individual contract. Participants received a $400 heat pump installation rebate, offered by the installer if 40 heat pump installations occurred through the campaign. Overall, the campaign facilitated 75 heat pump installations (including participants that went with another contractor or heat pump model) and 30 efficiency upgrades (including participants that went with another builder or did DIY upgrades). The campaign created 3 new jobs as the heat pump installer hired an administrative assistant and two apprentices over the course of the campaign. It also helped Juneau work toward achieving its renewable energy goal of 80% renewable energy for space heating by 2045 by upgrading houses from fuel oil to heat pumps powered by the hydropower electric grid. Researchers conducted four surveys to inform Thermalize Juneau and future energy campaigns. The first surveyed existing and prospective heat pump owners in Juneau to identify barriers the campaign could address and inform recruitment efforts. Entry and exit surveys provided information on participant demographics, goals, outcomes, and suggestions for improving future campaigns. And a final survey of community members who had not participated in Thermalize Juneau gave insight on ways future campaigns could include a greater diversity of participants so they could realize similar benefits. Researchers also used pre-campaign energy modeling to predict energy savings, which was then compared to the savings estimated through aggregation of heat pump assessments and energy audits, and later to actual energy savings of 10 participants who installed a heat pump and were able to provide complete energy use data sets. In addition to energy savings, and to assist the electric utility in future planning efforts, researchers analyzed the overall change in electric use across participants with energy data and heat pump installations. They also completed a life cycle cost analysis, showing positive net present values for those displacing a fuel oil appliance, and a more mixed case for those switching from electric baseboard. This project proved the feasibility of energy campaigns, with a goal of beneficial electrification, in cold, remote locations. The Thermalize Juneau team compiled a Guidebook to Thermalize Campaigns, available online. In addition to documenting what occurred in Alaska’s first thermalize campaign, it provides tips and resources for other communities wishing to implement a similar program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

bifiPV2020 Bifacial Workshop: A Technology Overview

The virtual bifiPV Workshop was held in July 2020 to provide the solar industry with a forum for sharing and discussing research into bifacial photovoltaic (PV) technology. This report outlines major insights from the workshop to give the reader an overview of the latest developments in bifacial PV technology worldwide, from the lab to the field. Citations are drawn from this workshop unless otherwise noted. Presentations for the bifiPV2020 Workshop focused on the following areas: bifacial power plant modeling and simulation, albedo improvements, the development of encapsulants, the durability and reliability of current bifacial technologies, performance comparisons between glass-glass and glass-transparent backsheet configurations, the future of passivated emitter and rear contact (PERC) solar cells, and the growing adoption of n-type solar cells. With 650 GW total PV installed worldwide and 1 TW to come very soon, PERC is now the standard PV cell type produced en masse. However, it is already reaching 23% efficiency, the upper limit for this type of technology. PV modules breaking the 0.5-kW barrier are starting to appear, and the costs of standard PERC technology are already below 0.2 USD/Wp. In 2019, five GW of bifacial PV were installed worldwide. In 2020, the majority of bifacial installations are expected to be located in the United States, China, and Middle East and North Africa (MENA) states. N-type bifacial technologies are becoming increasingly viable and have huge potential to dominate the market in the coming years. With bifacial technology mounted on horizontal single-axis trackers (HSAT), bids below 10 USD/MWh will soon be observed in the MENA region, and later in Chile and the United States. Factory audits and reliability testing can reduce field failures by helping buyers to select producers that follow rigorous quality assurance and quality control processes.

14 SOLAR ENERGY↗

bifiPV2020 Bifacial Workshop: A Technology Overview

The virtual bifiPV Workshop was held in July 2020 to provide the solar industry with a forum for sharing and discussing research into bifacial photovoltaic (PV) technology. This report outlines major insights from the workshop to give the reader an overview of the latest developments in bifacial PV technology worldwide, from the lab to the field. Citations are drawn from this workshop unless otherwise noted, with all proceedings available online at bifipvworkshop. com. Presentations for the bifiPV2020 Workshop focused on the following areas: bifacial power plant modeling and simulation, albedo improvements, the development of encapsulants, the durability and reliability of current bifacial technologies, performance comparisons between glass-glass and glass-transparent backsheet configurations, the future of passivated emitter and rear contact (PERC) solar cells, and the growing adoption of n-type solar cells. With 650 GW total PV installed worldwide and 1 TW to come very soon, PERC is now the standard PV cell type produced en masse. However, it is already reaching 23% efficiency, the upper limit for this type of technology. PV modules breaking the 0.5-kW barrier are starting to appear, and the costs of standard PERC technology are already below 0.2 USD/Wp. In 2019, five GW of bifacial PV were installed worldwide. In 2020, the majority of bifacial installations are expected to be located in the United States, China, and Middle East and North Africa (MENA) states. N-type bifacial technologies are becoming increasingly viable and have huge potential to dominate the market in the coming years. With bifacial technology mounted on horizontal single-axis trackers (HSAT), bids below 10 USD/MWh will soon be observed in the MENA region, and later in Chile and the United States. Factory audits and reliability testing can reduce field failures by helping buyers to select producers that follow rigorous quality assurance and quality control processes.

14 SOLAR ENERGY↗

Implementation of an ICS Ransomware Testbed: Scenarios, Variants, and Evaluation Methods

Ransomware attacks on Industrial Control Systems (ICS) have emerged as a formidable threat to the United States’ critical infrastructure, eliciting grave concerns regarding national security. In March 2023, the FBI Internet Crime Complaint Center (IC3) unveiled its 2022 Internet Crime Report, highlighting a concerning 870 complaints related to ransomware impacting U.S. critical infrastructure. Of the country's 16 critical infrastructure sectors, 14 encountered at least one ransomware attack. Notably, while the Healthcare and Public Health sector suffered the most, reporting 210 attacks, sectors pivotal to ICS networks and governmental organizations were also targeted: the Defense Industrial Base reported 1 attack, Water and Wastewater Systems 3, Chemical 19, Energy 15, Government Facilities 115, and Critical Manufacturing 157. For instance, a ransomware attack on a major chemical company could jeopardize not only its production but also pose environmental risks should systems controlling hazardous materials be compromised. In 2022, three ransomware variants predominantly targeted U.S. critical infrastructure: HIVE, with 87 attacks; ALPHV/BlackCat, with 114; and LOCKBIT, with 149. Several cyber-attacks, such as the MOVEit data breach in May 2023 and the Colonial Pipeline ransomware attack in May 2021, have been so impactful that they commanded national attention. The DarkSide hacking group's assault on the Colonial Pipeline, initiated on May 6th, 2021, stands as one of the most substantial and publicly acknowledged cyber-attacks against U.S. critical infrastructure. The group exploited an exposed Virtual Private Network (VPN) password, paving the way for initial intrusion and subsequent data theft. A mere day later, DarkSide unleashed a ransomware attack that compromised vital accounting and billing systems, prompting an immediate shutdown of the pipeline to mitigate further ransomware proliferation across its network. This crisis spurred a robust response from the U.S. president and regulators, culminating in a national emergency declaration related to the pipeline shutdown on May 9th, 2021. This incident mirrors the 2017 NotPetya ransomware attack that significantly impacted the shipping giant Maersk, highlighting an urgent need for fortified cybersecurity across various industries. Future incidents, akin to the Colonial Pipeline attack, could potentially be mitigated—or entirely averted—should government agencies and private entities scrutinize system vulnerabilities, exploring various ransomware types and entry points. Proactive measures, such as conducting experiments on VPN accounts or auditing passwords to pinpoint duplicate usage across diverse systems and software, might illuminate feasible entry points and vulnerability zones within an organization's systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

HAT m:N Cognitive Task Analysis (CTA)

This Cognitive Task Analysis (CTA) study was designed to understand the capability of the m:N Tactical Operator (TO) interfaces developed by the Human-Autonomy Teaming Laboratory at NASA Ames to support operators responsible for simplified pilot operations of 100 independently operated small UAS (sUAS) in a constrained geographic area. The m:N sUAS TO interface includes a central Tactical Situation Display (TSD) digital map with moving icons reflecting the sUAS location and planned flight route. The interface also has two side panels. The left panel includes a tabular list of UAS assets and mission tasking, a list of recently viewed assets, and a list of events and alerts. The right panel includes a tabular list of UAS assets and their associated telemetry, text-based chat communication window, and a tabbed checklist window. This CTA was adapted from the incident-based applied cognitive task analysis (Militello & Hutton, 1998) and included demographics questions, scenario-based simulations, a task diagram and knowledge audit methods. In addition to examining the support provided by this m:N sUAS TO interface, this CTA study, conducted with aviation subject matter experts in analogous roles to the future tactical operator, was designed to illuminate and project likely cognitive requirements of the tactical operator. Interviewees participated in two scenario-based simulations using the m:N sUAS TO interfaces. In the first simulation, the interviewees supervised 12 sUAS operating in downtown San Diego, California transiting to and from a central sUAS Hive, restaurant locations, and customer drop off locations. Interviewees were asked to react to a UAS Volume Reservation (UVR) event with a two-phase impact on food delivery operations. In the second scenario, the interviewees supervised 100 sUAS operating in the same airspace and with the same mission. Interviewees used the interfaces to recognize and react to two sUAS air vehicle problems. After each scenario, we asked the interviewees a semi-structured list of questions to elicit their reflections about using the interfaces. Interviewees were confident in their ability to respond to two off-nominal situations in each simulation. Interviewees felt that, given high levels of automation on the sUAS, they would be able to manage the events without requiring additional support or handing off the sUAS to a colleague or supervisor in both the n=12 or n=100 sUAS settings. In the n=12 sUAS condition, interviewees used the center map to understand the asset location and progress along with mission tasking. An additional display window, Asset Telemetry, helped interviewees understand battery state and sUAS altitude. When the number of sUAS increased, interviewees altered their behavior. Rather than maintaining awareness of individual assets, interviewees appeared to become more reactive, managing exceptions. Interviewees reported that they spent less time looking at the nominal aircraft, and focused their attention primarily on the off-nominal aircraft. In addition, in the second simulation with n=100 sUAS, interviewees reported that they relied more on the side panels (Mission Timeline and Asset Telemetry) to gather information.

human-autonomy teaming↗

How To Determine and Verify Operations and Maintenance Savings in Energy Savings Performance Contracts

Operations and maintenance (O&M) savings frequently occur in energy savings performance contracts (ESPCs). During FY 2022, 37% of reported annual cost savings for projects awarded under the U.S. Department of Energy (DOE) ESPC indefinite delivery indefinite quantity (IDIQ) contracts and in the performance period were due to O&M or other energy- and/or water-related cost savings, with the balance (63%) from utility cost savings (i.e., energy or water cost savings). Sometimes the energy- and water-related cost savings are acknowledged and included in payments within ESPCs; other times, for various reasons, they are not. As presented in this guide, FEMP recommends including energy- and water-related cost savings that are O&M (including related repair and replacement) savings in the financial aspects of an ESPC, to the extent such savings can be documented. Inclusion of these savings will help augment project scopes and/or lower interest costs (by shortening financing terms). However, there is a burden of proof as to what constitutes acceptability in O&M savings that needs to be carefully considered and documented in individual projects. Beyond promoting a key tenet used in U.S. federal performance contracting—that savings must be from actual budgets and therefore based on the level of O&M that is actually occurring, not what should have been performed—FEMP also recommends good practice in establishing and documenting O&M baselines, formulating the rationale for baseline adjustments during the performance period, and conducting ongoing verification activities. This document concludes with five examples of how O&M savings may be handled, in situations ranging from the partial displacement of O&M contracts to consolidation and “virtualization” of servers in data centers. A key theme that permeates this guide is the importance of thoroughly documenting all conditions and assumptions used in the development of and accounting for O&M costs and savings throughout the ESPC life cycle, from baseline-setting to measurement and verification (M&V) of the savings during each year of the performance period. Doing so not only prevents internal claims of non-performance (especially in the case of staff turnover during the contract term), but also simplifies ordering agency and energy service company (ESCO) response in the event of scrutiny from oversight organizations, such as government audits. While this guide focuses on federal ESPCs, it may also be applicable when O&M savings are included in utility energy service contracts (UESCs) and non-federal ESPCs.

Voss, Phil↗

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗