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At least 631 records · Page 35

Refinery Integration Analysis: Pathways, Challenges, and Opportunities

Integrating biomass-derived intermediates into traditional petroleum refineries presents unique challenges and opportunities, requiring innovative analysis approaches that account for biofuel producers and refiners. Consequently, teams within the National Renewable Energy Laboratory (NREL) have developed a comprehensive refinery integration analysis framework that combines experimental data, detailed techno-economic analyses of bio-conversion pathways, and economic projections within refinery linear programming (LP) optimization models. These models enable the identification of promising bio-integration strategies tailored to specific refinery configurations, economic conditions, and production goals. They also capture upstream and downstream impacts, highlighting critical bottlenecks and research opportunities for increasing the share of biogenic feedstocks in traditional refining operations. Refinery models are also packaged into a broader bio-economy optimization framework which enables biofuel supply chain optimization with standalone biofuel production and refinery co-processing/repurposing options. This presentation discusses promising refinery bio-integration strategies along with key challenges and opportunities identified using NREL's refinery and bio-economy optimization frameworks.

09 BIOMASS FUELS↗

Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in the electricity mix of the local electric grid to better understand the environmental impacts of electricity end users. We offer hourly estimates of the U.S. electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority through our publicly accessible tool, the Water Integrated Mapping of Power and Carbon Tracker (Water IMPACT). While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Strategies for Residential Energy Efficiency and Community Resilience for Floyd County, Kentucky

This report outlines the technical assistance provided to Floyd County Fiscal Court, Kentucky, and Vision Granted through the U.S. Department of Energy Clean Energy to Communities Expert Match Program. Floyd County, designated as “distressed” and “disadvantaged,” faces significant economic challenges, including limited job prospects, high energy costs, and youth “brain drain.” This technical assistance aims to address these pressing issues by implementing strategies to enhance home energy efficiency and livability while also aligning retrofit efforts with goals for resilience and workforce development. Through targeted guidance, this report aims to empower Floyd County residents and organizations in navigating resources for improving housing conditions, creating workforce opportunities, and enhancing resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗

Investigating Quantum Materials with Half-Polarized Diffraction and magnetic PDF analysis at the HB-2A Neutron Powder Diffractometer

Local magnetic ordering and anisotropy is often central to the emergent behavior and subsequent functional properties in quantum materials and beyond. Neutron powder diffraction provides a straightforward yet extremely powerful technique for quantitative measurements of microscopic magnetic properties. The HB-2A powder diffractometer located at the High Flux Isotope Reactor in ORNL is traditionally utilized for long-range magnetic structure determination. Recently these capabilities have been extended to include methods aimed at accessing local magnetism: Half- polarized neutron powder diffraction (pNPD) and magnetic pair distribution function (mPDF) analysis. These two distinct techniques are possible on HB-2A due to the versatility of the instrument’s reciprocal space coverage, resolution and novel ultra-low temperature multi-sample changers that operate down to dilution refrigerator temperatures. This provides unique capabilities not found on any powder diffraction instrument and is particularly well suited to investigations of magnetic quantum materials. The development and implementation of these techniques will be discussed with a series of science case examples ranging from geometric frustrated magnets to magnetic metal-organic frameworks. Data reduction and analysis tools will be presented that enable the extraction of the local site susceptibility tensor and local spin-spin correlations in real space. Finally, potential combinations of these techniques in the form of half-polarized magnetic pair distribution function (pmPDF) analysis will be considered. Looking forward, HB-2A is undergoing a detector upgrade that will be in the user program by 2026. This will offer an order of magnitude increase in count rates to further aid the development of these often low signal measurements and provide new scientific capabilities.

Neutron Scattering↗

Bike and Scoot to Transit

In this project, we developed a micromobility first-mile service for customers to access public transit. We launched this service as a pilot in the Seattle area that incentivized transit customers to bike or scoot to transit. The objective was to learn how to integrate different micromobility services and provide a unified reward program. Our pilot was called “Bike and Scoot to Transit” and ran from November 2022 to September 2023. More than a dozen locations were selected near transit hubs and light rail/train stations as preferred parking locations. Trips ending at those locations were partially funded. The pilot supported 19,226 qualified trips and distributed $73,000 in total benefits for the participants of the pilot. This dataset was collected from our pilot, which includes the following: - Monthly data: Monthly trip and funding summaries. - Data summary: Data broken down based on the micromobility service provider and equipment. - Trip data: List of all trips recorded during the pilot. - Pricing models: Fees charged by micromobility service providers. ![bike to transit](bike-transit.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reported Energy and Cost Savings from the DOE ESPC IDIQ Program: FY 2023

The objective of this work was to determine the realization rate of energy and cost savings from the U.S. Department of Energy’s (DOE’s) Energy Savings Performance Contract (ESPC) program based on information reported by the energy services companies (ESCOs) that are carrying out ESPC projects at federal sites. Information was extracted from 201 measurement and verification (M&V) reports covering 191 projects to determine reported, estimated, and guaranteed cost savings and the associated reported and estimated energy savings for the previous contract performance year. This report covers projects that had a performance year ending in fiscal year 2023, between October 1, 2022 and September 30, 2023, and had an M&V report issued. Additionally, the annual cost to perform M&V was extracted from the individual project Task Order (TO) Schedules.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A GPU-based compressible combustion solver for applications exhibiting disparate space and time scales

High-speed chemically active flows pose significant computational challenges due to their disparate space and time scales, with stiff chemistry often dominating simulation time. While modern scientific computing programs achieve exascale performance by leveraging graphics processing units (GPUs), existing GPU-based compressible combustion solvers face critical limitations in memory management, load balancing, and handling the highly localized nature of chemical reactions. To this end, we present a high-performance compressible reacting flow solver built on the AMReX framework and optimized for multi-GPU settings. Here, our approach addresses three GPU performance bottlenecks: memory access patterns through column-major storage optimization, computational workload variability via a bulk-sparse integration strategy for chemical kinetics, and multi-GPU load distribution for adaptive mesh refinement applications. The solver adapts existing matrix-based chemical kinetics formulations to multi-grid contexts. Using representative combustion applications, including 2D and 3D detonations and a 3D jet-in-crossflow configuration, we demonstrate 1.4–5× performance improvements over initial implementations on an in-house cluster of NVIDIA H100 GPUs, and near-ideal weak scaling on the Frontier supercomputer (Oak Ridge Leadership Computing Facility) with up to 1024 AMD Instinct MI250X GPUs. Roofline analysis reveals substantial improvements in arithmetic intensity for both convection (∼ 10 ×) and chemistry (∼ 4 ×) routines, confirming efficient utilization of GPU memory bandwidth and computational resources.

42 ENGINEERING↗

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Meso-scale modeling of UO2 nuclear fuel to high burnup

To improve the economics of light water reactors for commercial nuclear energy generation, utility operators are seeking to obtain regulatory approval to run UO2 fuel to higher levels of burnup. One potential impediment to obtaining this approval is the phenomenon of fuel fragmentation, relocation, and dispersal (FFRD). FFRD can result when fuel experiences a rapid temperature transient, such as that occurring during a Loss Of Coolant Accident (LOCA). FFRD has historically been most associated with the rim region in UO2 fuel pellets, where the phenomenon of fragmentation is also referred to as pulverization due to the small size of the fragments. More recent evidence suggests that the so-called “dark zone” (due to its appearance in micrographs) that can be observed in the mid-radial regions of high burnup fuel is also susceptible to FFRD. Although empirical fuel performance models have been developed that can adequately predict pulverization in the rim region under typical LWR conditions, a scientific understanding of what underlies fuel restructuring and subsequent FFRD is lacking even in the rim region, and no models are currently available for the behavior the dark zone. To address these challenges, the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has employed a multi-scale modeling approach to improve scientific understanding and develop new fuel performance models. In this talk, I will focus on meso-scale efforts, which form a crucial link between atomic-scale and engineering-scale models. Phase-field modeling combined with cluster dynamics is used to predict the restructuring process in the rim region. Phase-field fracture modeling, informed by atomistic simulations, is used to predict the onset of pulverization in the rim region. Combining these techniques together allows the extent of rim pulverization to be predicted. The formation and evolution of the dark zone has also been simulated with the phase-field method, using an improved approach to vacancy source term parameterization. The work shows the important impact of microstructure on fuel performance.

fracture↗

U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) (Final Technical Report)

The University of Illinois Chicago (UIC) was awarded the U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) program to provided technical and policy expertise to support local opportunities to promote CHP, waste heat to power, district energy, and microgrids in the Midwest and Central regions of the U.S. that included the states of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, Ohio, and Wisconsin. During this contract period, UIC, through the Midwest CHP TAP activities, provided significant regional support to the U.S. strategic goals of: 1) Stimulating America’s Energy Revolution and Promoting Energy Independence; 2) Promoting Jobs and Manufacturing Competitiveness; 3) Supporting a Positive Trade Balance; 4) Enhancing Energy System Resiliency and Energy Security; and 5) Improving the Nation’s Infrastructure. UIC met the annual go/no-go metrics each year and either met and/or exceeded the milestones each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NARUC Resilience Framework

The NARUC Resilience Framework provides state regulators and other key stakeholders with a structured approach to considering policies and programs that will enhance grid resilience amid evolving technological, environmental and economic challenges. This Framework consolidates insights from nationwide workshops and peer discussions into six actionable components: (1) setting goals and objectives, (2) leveraging use cases, (3) establishing shared definitions, (4) ensuring inclusive process leadership, (5) addressing critical design questions, and (6) guiding implementation. This Framework is intended as a strategic tool for regulators to navigate resilience investments, prioritize affordability, integrate stakeholder needs, and foster collaboration across agencies, all while balancing cost-effectiveness with societal and economic resilience outcomes. By presenting a structured approach to decision-making rather than prescriptive solutions, the Framework supports nuanced, jurisdiction-specific resilience planning and is adaptable to the dynamic demands of modern energy systems

24 POWER TRANSMISSION AND DISTRIBUTION↗

Separate, separated, and together: the transcriptional program of the Clostridium acetobutylicum-Clostridium ljungdahlii syntrophy leading to interspecies cell fusion

ABSTRACT Syntrophic cocultures (hitherto assumed to be commensalistic) of Clostridium acetobutylicum and Clostridium ljungdahlii , whereby CO 2 and H 2 produced by the former feed the latter, result in interspecies cell fusion involving large-scale exchange of protein, RNA, and DNA between the two organisms. Although mammalian cell fusion is mechanistically dissected, the mechanism for such microbial-cell fusions is unknown. To start exploring this mechanism, we used RNA sequencing to identify genes differentially expressed in this coculture using two types of comparisons. One type compared coculture to the two monocultures, capturing the combined impact of interactions through soluble signals in the medium and through direct cell-to-cell interactions. The second type compared membrane-separated versus -unseparated cocultures, isolating the impact of interspecies physical contact. While we could not firmly identify specific genes that might drive cell fusion, consistent with our hypothesized model for this interspecies microbial cell fusion, we observed differential regulation of genes involved in C. ljungdahlii’s autotrophic Wood-Ljungdahl pathway metabolism and genes of the motility machinery. Unexpectedly, we also identified differential regulation of biosynthetic genes of several amino acids, and notably of arginine and histidine. We verified that they are produced by C. acetobutylicum and are metabolized by C. ljungdahlii to its growth advantage. These and other findings, and notably upregulation of C. acetobutylicum ribosomal-protein genes, paint a more complex syntrophic picture and suggest a mutualistic relationship, whereby beyond CO 2 and H 2 , C. acetobutylicum feeds C. ljungdahlii with growth-boosting amino acids, while benefiting from the H 2 utilization by C. ljungdahlii . IMPORTANCE The construction and study of synthetic microbial cocultures is a growing research area due to the untapped potential of defined multi-species industrial bioprocesses and the utility of defined cocultures for generating insight into complex, undefined, natural microbial consortia. Our previous work showed that coculturing C. acetobutylicum and C. ljungdahlii leads to a unique metabolic phenotype (production of isopropanol) and heterologous cell fusion events. Here, we used RNAseq to explore genes involved in and impacted by these fusions. First, we compared gene expression in coculture to each monoculture. Second, we utilized a transwell system to compare gene expression in mixed cocultures to cocultures with both species physically separated by a permeable membrane, isolating the impact of interspecies “touching” on the transcriptome. This study deepens our mechanistic understanding of the C. acetobutylicum-C. ljungdahlii coculture phenotype, laying the groundwork for reverse genetic studies of heterologous cell fusion in Clostridium cocultures.

Willis, Noah B. (ORCID:0009000689365955)↗

The relationship between stress, anxiety and eating behavior among Chinese students: a cross-sectional study

Background The expansion of higher education and the growing number of college students have led to increased awareness of mental health issues such as stress, anxiety, and eating disorders. In China, the educational system and cultural expectations contribute to the stress experienced by college students. This study aims to clarify the role of anxiety as a mediator in the relationship between stress and eating behaviors among Chinese college students. Methods This study utilized data from the 2021 Psychology and Behavior Investigation of Chinese Residents, which included 1,672 college students under the age of 25. The analysis methods comprised descriptive statistics, t -tests, Pearson correlation analyses, and mediation effect analysis. Results The findings indicate that Chinese college students experience high levels of stress, with long-term stress slightly exceeding short-term stress. Both types of stress were positively correlated with increased anxiety and the adoption of unhealthy eating behaviors. Anxiety was identified as a significant mediator, accounting for 28.3% of the relationship between long-term stress and eating behavior (95% CI = 0.058–0.183). The mediation effect of short-term stress on eating behavior through anxiety was also significant, explaining 61.4% of the total effect (95% CI = 0.185–0.327). Conclusion The study underscores the importance of stress management and mental health services for college students. It recommends a comprehensive approach to reducing external pressures, managing anxiety, and promoting healthy eating behaviors among college students. Suggestions include expanding employment opportunities, providing career guidance, enhancing campus and societal support for holistic development, strengthening mental health services, leveraging artificial intelligence technologies, educating on healthy lifestyles, and implementing targeted health promotion programs.

Chai, Yulin↗

Zero-Emissions Roadmap for Oakland County

This document outlines a strategic pathway for Oakland County, Michigan to achieve zero emissions by 2050 under the Clean Energy to Communities (C2C) Program. The report encompasses analyses and high-level modeling to guide Oakland County in its emission reduction goals. Key methods include establishing an emissions inventory baseline with ongoing evaluation of future projects’ emissions impacts. Core elements include decommissioning old infrastructure, enhancing energy efficiency, deploying hybrid and ground-source heat pumps, and transitioning to electric fleets. It is proposed to structure the planning process into 5-year strategic plans to make the decarbonization process manageable. The document also emphasizes the need for reassessment of goals and periodic updates to remain adaptive to technological advancements and funding considerations. A matrixed approach for evaluating projects by cost and emissions savings is suggested to optimize decision-making given finite resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chicago Energy Efficiency Planning and Analysis and Integrated Retrofit Strategy Validation in Single-Family Homes

In June 2020, the project team comprised of Elevate and the National Renewable Energy Laboratory (NREL), with advisory roles from the City of Chicago and Commonwealth Edison, initiated a three-year project with the U.S. Department of Energy to inform communitywide energy planning at a local scale and validate advanced retrofit packages that achieve at least 50% energy savings in existing homes. The project team has characterized Chicago’s single-family and 2-4 unit housing stock and energy use using the ResStock™ modeling tool, and with that information developed advanced whole home energy retrofit packages for single family and 2-4 unit homes that can reduce energy use by at least 50% and support climate, air quality, and other goals. This report presents an analysis of the technical potential of applying these retrofit packages at a City-wide scale, and a roadmap for rapidly scaling up retrofit programs to improve Chicago’s housing stock and target investments in the neighborhoods that need it most. The main goals of the analysis are to: 1) develop a Chicago-specific single-family and 2-4 unit building retrofit prioritization strategy; 2) identify opportunities for beneficial electrification in communities and home types that stand to benefit most; and 3) assess costs and savings potential for retrofit investments at a household and city scale, in terms of energy use, bill impacts, carbon emissions, and other outcomes.

14 SOLAR ENERGY↗

Cyber Labeling for Energy Industrial IoT

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security and Emergency Response (CESER), at the request of the Deputy National Security Advisor for Cyber and Emerging Technologies, Anne Neuberger, initiated research in 2023 to develop a cybersecurity labeling proof-of-concept for energy products to expand on the Federal Communications Commission’s (FCC) proposed U.S. Cyber Trust Mark program. DOE mobilized researchers from six National Laboratories to develop and gather feedback on a proof-of concept label for solar inverters and smart meters, which serve as representative products for market-facing energy sector Industrial Internet of Things (IIoT). This report details the research team’s process across two phases and the resulting findings, which include challenges facing cyber labeling programs and recommendations to implement an expanded IIoT cyber labeling program in the U.S.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗