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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗

7. International Conference on the Foundations of Systems Biology in Engineering FOSBE 2018

The 7th FOSBE conference was held August 5-8 at the Hilton Chicago Oak Brook Hills Resort & Conference Center, in Chicago, Illinois. The conference was sponsored by CACHE, with technical co-sponsorship from IFAC Biosystems and Bioprocesses (TC 8.4), AIChE’s Society of Biological Engineering, and IEEE’s Control Systems Society. 83 participants from 11 countries met for the event; approximately 5% of participants were from industry and 43% were from countries outside the U.S. The meeting opened with a welcome reception Sunday evening, which was followed by Dr. Nathan Price, Systems Biology Institute, delivering the conference-opening lecture, “Mining Personal, Dense, Dynamic Data Clouds to Enhance Health and Drive Discovery”.

59 BASIC BIOLOGICAL SCIENCES↗

Design and Development of the Handling Frame Assembly Table for the National Ignition Facility Blast Shields

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.

42 ENGINEERING↗

MORS Phalax Ad for Systems Analysis

At Lawrence Livermore National Laboratory, applying cutting-edge science and technology to challenging security questions is an everyday thing. Systems Analysis is one way we solve problems—by bringing analytic rigor to missions like strategic deterrence and critical infrastructure defense. Working with the brightest minds in science, technology, and engineering, systems analysts at LLNL bring state-of-the-art analytic tools to bear on problems of national importance. From ensuring the safety, security, and effectiveness of our nation’s nuclear stockpile to shaping the future of inertial fusion energy—if you have a penchant for problem-solving using modeling and analysis tools—we have a place for you.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Design and Development of the Handling Frame Assembly Table for the NIF Sustainment Project (Draft)

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The NIF Sustainment project's goal is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, design analysis and validation, and final design. Future work will focus on building and commissioning the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Direct Air Capture of CO2 (DAC) [Tech Snapshot]

Researchers at Los Alamos have extensive capabilities in design, testing and optimization of: (1) new capture materials based on membrane separation, amine and other solvent and sorbent separation, and porous materials; (2) biological capture methods, particularly algae and plants; (3) full-scale systems using science-based virtual learning; and (4) system performance under specific meteorological conditions, impacts of CO2 capture via atmospheric data and simulations, and availability of energy and storage capacity. The goal for Los Alamos is advancing our physical technologies and engineered systems approaches from the development phase to a minimal viable product in the energy sector for commercial purposes. Los Alamos is seeking strategic commercialization partners to work with us in advancing these capabilities and technologies for commercial viability.

54 ENVIRONMENTAL SCIENCES↗

Integration of a Wigner effect-based energy storage system with an advanced nuclear reactor

In this work, an innovative energy storage concept based on the purposeful creation of defects in crystalline material by neutron irradiation is presented. Lattice defects are generated when heavy particles collide with the atoms in a crystal structure, i.e., if the incoming particles have enough energy, recoil atoms are displaced from their initial lattice sites. Most of the displaced atoms will eventually combine with nearby vacancies, but some of them will come to rest in non-ideal locations. The energy held by displaced atoms is called Wigner energy. Lattice defects can migrate and form clusters, and the Wigner energy can be released from these groupings if sufficient activation energy is provided. In the nuclear industry, this effect is well-known since it represented an issue for graphite-moderated reactors. This work presents the conceptual design of an engineering system that exploits this physical process to store the energy of neutrons in advanced reactor concepts. In the first part of the paper, the theoretical performance of an energy storage system based on the Wigner effect is described. Given the lattice properties and the compatibility with the harsh reactor environment, graphite was selected as the candidate material for the irradiation targets. Both experimental data and molecular dynamics simulations confirmed that this system can achieve performance comparable with state-of-the-art batteries in terms of stored energy density. In the second part of the paper, the engineering challenges of this innovative technology and the proposed solutions are described. After defining the optimal irradiation conditions, the different steps of the operation of the proposed energy system (from energy storing to energy harvesting) were defined. Finally, the integration of this concept with advanced reactor designs, i.e., a Sodium-cooled Fast Reactor and a Molten Salt-cooled Reactor, was investigated and the corresponding performance was evaluated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity)

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity) project aims to demonstrate a novel, scalable method for removing carbon dioxide (CO 2 ) directly from ambient air and delivering it to cyanobacterial cultures to produce commodity biofuel, mid-value protein for supplements, and high value phycocyanin (PC), a natural blue colorant (Figure A). This approach uses low-cost, reusable anion exchange polymers embedded in modular mesh packets, which capture CO 2 during drying cycles when exposed to ambient air, and release concentrated CO 2 into aqueous cultivation systems. The project addresses a critical challenge in energy research needed for developing sustainable, economically viable methods of Direct Air Capture (DAC) that can be integrated with bio-based systems for fuel and chemical production. AUDACity contributes to scientific understanding by integrating materials chemistry, cyanobacterial biology, and system engineering to create a distributed CO 2 delivery platform. Key insights have emerged around the design of biocompatible sorbents, optimization of CO 2 capture-release cycles, and durability of packet-based delivery systems under outdoor conditions. Notably, the team has synthesized and tested a range of polymer sorbents, identified mechanisms of material degradation and fouling, and advanced both lab- and pilot-scale cultivation systems to evaluate performance. From a technical and economic standpoint, AUDACity shows promise for achieving cost-effective CO 2 capture and delivery into aqueous media and biofuel production. Preliminary techno-economic analysis (TEA) indicates that the DAC system based on current performance can reach $\$$680/tonne CO 2 delivered into aqueous solution; with reasonable improvements to sorbent lifetime, sorbent capacity, reducing water uptake the approach could reach $\$$66/tonne by avoiding the need for energy-intensive sorbent regeneration and CO 2 compression, making it more feasible for decentralized deployment. With these costs for CO 2 and by extracting and selling high-value PC ($\$$50/kg) and mid-value protein supplement ($\$$6/kg), the remaining biomass can be hydrothermally treated into biofuel for $\$$2.50/gallon, and would support a small first-of-a-kind biorefinery capable of producing 500 barrels per day of biofuel. The project offers meaningful public benefits by advancing carbon removal technologies that are low-energy, modular, and adaptable to non-arable land and brackish water use. It aligns with national goals to develop advanced biotechnology and supports future pathways for bio-based fuels and products. By enabling direct coupling of CO 2 transfer into aqueous medium and biological carbon utilization, AUDACity lays the groundwork for effective algae cultivation without wasteful CO 2 delivery and is a promising and innovative solution for low-carbon fuel and bioproduct generation contributing to a vigorous bioeconomy.

09 BIOMASS FUELS↗

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Towards Semantic Search in Building Sensor Data

This paper presents a search engine system for sensor time series data and metadata in the context of building management. It takes natural language queries as input, retrieves sensor time series data, ranks them with respect to their relevance to a given query, and visualizes the time series as search results. In addition, the system allows users to interact with the search results: they can define events of interest in the visualized results and search across sensor data for similar events, i.e., the search by example scheme. Quantitative evaluations and user studies demonstrate the value of this system for managing building sensor data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Climate Influences on Capacity Expansion Planning with Application to the Western U.S

Electric power system planners utilize a variety of planning tools to inform decisions concerning generation and transmission additions to the electric grid, the need for operational changes, and to evaluate potential stressors on the system. Numerous factors contribute to the planning process including projected fuel and technology costs, policy and load profiles. There is also a growing recognition of the interdependency of the electric grid with other natural and engineered systems. Here we explore how future climate change and hydropower operability might influence decisions related to electricity capacity expansion planning and operations. To do so we assemble a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on future water supply for thermoelectric and hydropower generation. Separately, temperature impacts on electricity load are evaluated. Together, these climate factors spatially constrain a capacity expansion model that projects generation and transmission additions to the grid. The projected new capacity-builds are then evaluated on their operations, reliability, and cost under average and extreme climate conditions using production cost modeling. This coupled framework is demonstrated on the electric grid in the Western U.S., supporting capacity expansion planning by WECC, the North American Electric Reliability Corporation (NERC) regional entity responsible for reliability assurance of the Western Interconnection. This region was selected in part because the West is unique in that it has high potential for renewable penetrations and is experiencing large retirements/displacements of baseload resources, primarily coal, leading to possible operational challenges in terms of changing resource mix and the need for resource flexibility. Toward this challenge, planning scenarios encompass a range of alternative energy, climate and drought futures. In this context we explore answers to two strategic questions: 1) How does changing climate influence electricity expansion planning (generation and transmission) and future operations, including type and capacity of new builds, system reliability, cost and environmental impacts? 2) How does the representation of hydropower in the modeling framework influence the evaluation of bulk power system operations? Results indicate that climate has a measurable influence on recommendations concerning the capacity, type and location of new generation and transmission additions, with up to 17 GW additional capacity needed by 2038 to meet peak loads (~6.6% increase over capacity-builds based on historical climate). The extent of additional infrastructure needs is strongly influenced by future water availability for hydropower and the potential deployment of demand response technologies. Systems designed for future climate conditions were found to maintain high system reliability under a range of electricity and water availability scenarios (including significant drought), with minimal system curtailments. Additional capacity needs due to higher load tend to increase cumulative 20-year investment and operating costs by $\$$5-$\$$17 billion and generation costs increase by 9 to 19%. Finally, changing the representation of hydropower flexibility has a relatively small influence on capacity expansion in the Western Interconnection through 2038, but hydropower flexibility impacts generation costs to a similar extent as climate.

13 HYDRO ENERGY↗

Using Visual Systems Mapping to Improve Transparency and Comparability of Life Cycle Assessment Baseline Scenarios

Visual systems mapping is a systems engineering approach used to represent complex processes and interactions. This study evaluates its application for documenting assumptions in life cycle assessment (LCA) baseline scenarios. In LCA, the baseline or reference case represents the business as usual system against which changes in impacts (e.g., emissions) are assessed. These baseline assumptions are particularly influential in biomass LCAs, yet they often vary across studies due to regional context, system boundaries, and simplifying assumptions that are not consistently or transparently documented. As a result, key feedbacks, omitted processes, and boundary choices may remain unclear, limiting comparability across studies and weakening their usefulness for decision-making. This study examines whether visual systems mapping can improve the transparency and comparability of biomass LCA baseline scenarios. A case study of five published biomass-related LCAs were reviewed, and their baseline scenarios were translated into visual system maps to identify included processes, omitted components, and underlying assumptions. The analysis demonstrates that visual systems mapping can make baseline assumptions more explicit, highlight excluded dynamics, and improve documentation of system boundaries. Based on these findings, the study recommends the use of visual systems mapping alongside open data repositories and reproducible workflows to support greater transparency, reproducibility, and comparability in LCAs. These improvements can strengthen the role of LCAs in informing decisions related to sustainable biomass systems.

Davis, Maggie [ORNL] (ORCID:0000000181319328)↗

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

59 BASIC BIOLOGICAL SCIENCES↗

Quantifying the Impacts of Grain-scale Heterogeneity on Mechanical Response

Driven by the exceedingly high computational demands of simulating mechanical response in complex engineered systems with finely resolved finite element models, there is a critical need to optimally reduce the fidelity of such simulations. The minimum required fidelity is constrained by error tolerances on the simulation results, but error bounds are often impossible to obtain a priori. One such source of error is the variability of material properties within a body due to spatially non-uniform processing conditions and inherent stochasticity in material microstructure. This study seeks to quantify the effects of microstructural heterogeneity on component- and system-scale performance to aid in the choice of an appropriate material model and spatial resolution for finite element analysis.

36 MATERIALS SCIENCE↗

Design and License Application Development for TRISO-X (Final Scientific Technical Report)

This is the final progress report submitted by X-energy, LLC (XE) to the Department of Energy in support of cooperative agreement DE-NE0008745. This report provides a high-level summary of the work performed during the entire period of performance, running from August 24, 2018 – August 22, 2022. This span of time covers the original 3-year award and a one year no-cost extension. There were five tasks within this project: (1) project management, (2) systems engineering and studies, (3) TRISO-X Facility design, (4) facility license application development, and (5) support to application review. Detailed reporting during execution of the project was provided by a total of 16 quarterly reports, voluntary monthly update presentations, and annual summary presentations. Technical work products include 103 X-energy technical reports, 38 subcontractor (Centrus technical reports), 75 Nuclear Criticality Safety Evaluations/Calculation reports, and 272 miscellaneous design documents (e.g., Engineering Service Orders, Engineering Component Specifications, Procedures, Guidelines/Policies, Design and Interface Requirements documents, and Drawings). All 29 of the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2018, Work Breakdown Structure F.OA – Industry FOA FY 2018 Awards, F.03 – X-Energy TRISO-X Project. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

H2Integrate [SWR-23-31]

H2Integrate(H2I) is an open-source Python package for hybrid systems engineering design and technoeconomic analysis. It models and optimizes hybrid energy plants that produce electricity, hydrogen, ammonia, steel, and other products. H2Integrate is designed to be flexible and extensible, allowing users to create their own components and models for various energy systems. The tool currently includes distributed energy generation (wind, solar, wave, tidal), battery storage, hydrogen, ammonia, methanol, and steel technologies. Other elements such as desalination systems, pipelines, compressors, and storage systems can also be included as developed by users. Some modeling capabilities in H2Integrate are provided by integrating existing tools, such as HOPP, PySAM, ORBIT, and ProFAST. The H2Integrate tool is built on top of NASA's OpenMDAO framework, which provides a powerful and flexible environment for modeling and optimization.

King, Jennifer [National Renewable Energy Laborato↗

Commission < 5 µm spatial resolution x-ray imager for High Resolution Turbulence experiments

This report presents the successful development, commissioning, and deployment of the Scintillation-Based X-ray Imager (SBXI) for the High-Resolution Turbulence (HRT) campaign at the National Ignition Facility (NIF). The SBXI system was designed to overcome the spatial resolution and efficiency limitations of conventional x-ray imaging detectors. Through careful system engineering, rigorous laboratory characterization, and experimental validation at NIF, the SBXI has demonstrated spatial resolution at the object plane of 5 μm (±0.5 μm) and a detective quantum efficiency (DQE) of 34% at 7.2 keV, both of which surpass the requirements set by the campaign, and meeting the L2 milestone. The system’s deployment enables high-fidelity imaging of fine-scale hydrodynamic instabilities, directly supporting advanced turbulence model validation and future high energy density physics research.

42 ENGINEERING↗