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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 181 records · Page 10

Transforming Energy Through Sustainable Mobility: Expanding Low-Carbon Transportation R&D Solutions

As the nation's premier laboratory for cutting-edge transportation decarbonization research and development solutions, the National Renewable Energy Laboratory (NREL) pioneers the creation and deployment of sustainable mobility technologies and strategies, with a focus on slashing transportation sector greenhouse gas emissions and combatting climate change. Trucks, planes, cargo ships, and other difficult-to-decarbonize vehicles are part of this essential transition for the transportation sector, which is currently the nation's largest source of the greenhouse gas emissions. NREL provides the scientific building blocks needed to spur innovation through multifaceted analysis, research, and engineering. This work acts as a catalyst to help industry bring affordable, high-performance, energy-efficient, and low-emission modes of transport and related infrastructure to market sooner. Our researchers collaborate closely with academic, government, and industry partners to design better batteries, drivetrains, and engines. They develop technologies for high-power charging, thermal management, energy storage, and power electronics. They are also reimagining fuels and combustion while creating sustainable lightweight materials. Unbiased expert guidance - backed by credible data and analysis, tools, and scientific rigor - empowers partners to make informed decisions about sustainable transportation. NREL recognizes that communities with limited mobility options face reduced access to employment opportunities, health care, and education, lowering overall quality of life. Alongside partners, NREL experts are creating transportation solutions that meet community-identified needs and increase mobility equity in historically underserved and overburdened communities. Rather than providing a one-size-fits-all solution, we take an interdisciplinary approach to mobility equity that considers the needs and challenges of diverse groups, maximizing benefits at the individual, community, and societal levels.

ADVANCED PROPULSION SYSTEMS↗

Multiphysics Design Optimization and Additive Manufacturing of Nuclear Components (Final CRADA Report - Executive Summary)

Westinghouse Electric Company (WEC) actively participated in the advancement of the nuclear fuel and reactor design space and requested the help of Oak Ridge National Laboratory (ORNL) in the creation of a new design tool set. This report details the creation of a collection of software tool sets that are linked together to collectively assist WEC design engineers in developing novel ideas outside the normal scope of traditional nuclear fuel and reactor design formulas. Specifically, Siemens HEEDS, a design space exploration and parametric optimization software, monitored and changed parameters in a collection of softwares to meet the team’s objective. The HEEDS parametric optimization method, SHERPA, was developed to control the Siemens NX CAD platform to adjust the native CAD of a hexahedral spacer grid. This new geometry can be used to execute a topological design optimization by the NX Topology software add-in. The resulting geometry is additively manufacturable. This topological optimization occurred twice—once on the spacer grid’s spring, and once on the dimple geometry. These new geometries were imported by Siemens’ STAR-CCM+, a multiphysics structural and fluid dynamic computational solver in which the spring geometry is deflected to match the rod insertion configuration. Along with the dimple geometry, this new deflected spring was used to complete a hydraulic assessment of a single-unit cell comprising one rod, one spring, and two dimples. The HEEDS SHERPA algorithm ranks the design based on the final mass of the unit cell and the hydraulic pressure drop performance. The ORNL team demonstrated the ability to use this software and provided engineering judgement to apply modern aerospace aerodynamic design. The effort has been focused on thinking outside the conventional design space and redesigning a spacer grid to perform beyond the WEC set objectives. Furthermore, the ORNL team also demonstrated that the HEEDS optimization routine can independently develop a design that meets the WEC design goals. Although these designs were at a low technology readiness level, their demonstration confirmed the team’s capability to create novel advanced nuclear concepts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Metabolic engineering strategies to produce medium-chain oleochemicals via acyl-ACP:CoA transacylase activity

Abstract Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation - an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads , that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Freeze range of a condensing gas propagating in a liquid helium-cooled tube

Understanding air propagation and condensation following a catastrophic vacuum break in particle accelerator beamlines cooled by liquid helium is crucial for maintaining the operational safety of these facilities. Previous experimental investigations on nitrogen gas propagation in both normal liquid helium (He I) and superfluid helium (He II) cooled copper tubes unveiled a nearly exponential deceleration of the gas propagation. A comprehensive theoretical model incorporating gas dynamics, heat transfer, and condensation mechanisms has been developed, which effectively reproduces various key experimental observations. An intriguing phenomenon uncovered in our model simulation is that the gas propagation appears to nearly stop beyond a certain distance from the location where condensation starts. We refer to this distance as the freeze range. In this paper, we present our systematic study of the freeze range at various inlet mass fluxes and tube diameters. We show that the results can be well described by a simple correlation. The underlying physical mechanism that supports this useful correlation is explained. Knowing the freeze range may allow accelerator engineers to develop protocols for controlling frost-layer contamination in the beamline tubes, which is of great practical importance.

43 PARTICLE ACCELERATORS↗

Co-Design of a Fully Electric Hybrid Hydraulic-Electric Architecture (FE-HHEA) for Off-Road Mobile Machines

Off-road mobile machines, such as excavators and wheel-loaders, are typically actuated by hydraulics using internal combustion engines as their power sources. There is a trend towards fully electrifying these machines and improving their efficiencies due to environmental regulations and concerns. In this paper, a control co-design methodology is used to design a Fully Electrified Hybrid Hydraulic-Electric Architecture (FE-HHEA) for an excavator that drastically reduces energy consumption and minimizes the sizes of costly electric components. By optimizing both control operation and the physical design, the co-design methodology takes into account the interaction between these two aspects. The design methodology also illustrates how the system architecture evolves from the previously developed IC engine powered HHEA with the engine replaced by an electric motor to a seemingly very different architecture with fewer components. The optimized system reduces energy consumption by 71% over the baseline system and uses electrical components that are 1/3 the size of an alternate fully electric architecture.

33 ADVANCED PROPULSION SYSTEMS↗

Investigating the Origins of Cyclic Variability in Internal Combustion Engines Using Wall-Resolved Large Eddy Simulations

Modern internal combustion engines (ICE) operate at the ragged edge of stable operation characterized by high cycle-to-cycle variations (CCV). A key scientific challenge for ICE is the understanding, modeling, and control of CCV in engine performance, which can contribute to partial burns, misfire, and knock. The objective of this study is to use high-fidelity numerical simulations to improve the understanding of the causes of CCV. Nek5000, a leading high-order spectral element, open source code, is used to simulate the turbulent flow in the engine combustion chamber. Multicycle, wall-resolved large-eddy simulations (LESs) are performed for the General Motors (GM), Transparent Combustion Chamber (TCC-III) optical engine under motored operating conditions. The mean and root-mean-square (rms) of the in-cylinder flow fields at various piston positions are validated using particle image velocimetry (PIV) measurements during the intake and compression strokes. The large-scale flow structures, including the swirl and tumble flow patterns, are analyzed in detail and the causes for cyclic variabilities in these flow features are explained. The energy distribution across the different scales of the flow are quantified using one-dimensional (1D) energy spectra, and the effect of the tumble breakdown process on the energy distribution is examined. Finally, the insights from this study can help us develop improved engine designs with reduced cyclic variabilities in the in-cylinder flow leading to enhanced engine performance.

33 ADVANCED PROPULSION SYSTEMS↗

Unprecedented non-hysteretic superelasticity of [001]-oriented NiCoFeGa single crystals

Superelasticity associated with the martensitic transformation has found a broad range of engineering applications. However, the intrinsic hysteresis and temperature sensitivity of the first-order phase transformation significantly hinder the usage of smart metallic components in many critical areas. In this paper, we report a large superelasticity up to 15.2% strain in [001]-oriented NiCoFeGa single crystals, exhibiting non-hysteretic mechanical responses, a small temperature dependence and high-energy-storage capability and cyclic stability over a wide temperature and composition range. In situ synchrotron X-ray diffraction measurements show that the superelasticity is correlated with a stress-induced continuous variation of lattice parameter accompanied by structural fluctuation. Neutron diffraction and electron microscopy observations reveal an unprecedented microstructure consisting of atomic-level entanglement of ordered and disordered crystal structures, which can be manipulated to tune the superelasticity. The discovery of the large elasticity related to the entangled structure paves the way for exploiting elastic strain engineering and development of related functional materials. NiCoFeGa single crystals exhibit large non-hysteretic superelasticity over broad temperature and composition ranges. It is attributed to the continuous phase transition with applied stress, which is related to the fluctuation of entangled ordered and disordered crystal structures.

36 MATERIALS SCIENCE↗

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

99 - GENERAL AND MISCELLANEOUS↗

Development of the high energy engineering X-ray (HEX) superconducting wiggler, magnetic measurement, installation, and commissioning

The High energy Engineering X-ray (HEX) diffraction beamline at the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Lab (BNL) is the first high-energy beamline capable of reaching 200 keV for a monochromatic beam. With the 3 GeV electron beam energy for the NSLS-II ring, only the superconducting wiggler (SCW) producing greater than 4 T peak field can cover these ranges with a sufficient number of photons. The 1.2 m-long HEX-SCW has a period length of 70 mm and a field strength on-axis of 4.3 T. It utilizes no liquid helium, and the vertical aperture size of the electron beam vacuum chamber is 8 mm. Unlike regular undulators/wigglers, there is no standard configuration for the magnetic measurement system for superconducting insertion devices. The NSLS-II Insertion Devices group has developed, in collaboration with the vacuum group, a novel in-vacuum Hall mapper with a 1.75 m in-vacuum linear motor and an in-vacuum flip coil system utilizing many commercial-off-the-shelf products. The measurements were conducted at the BNL, and the device was installed in the ring and commissioned. Here, this paper provides a description of the SCW and its magnetic measurement systems, as well as a brief account of the installation and commissioning efforts.

36 MATERIALS SCIENCE↗

LANL Test Engineering’s Structural Dynamics Research and Development Efforts [Slides]

LANL's priority roles are serving as a nuclear weapons design agency and a nuclear weapons production agency; addressing nuclear threats; and performing national security science, technology, and engineering. LANL’s Test Engineering organization serves the national mission of maintaining a strategic nuclear deterrent by providing high-quality, empirical evidence through the execution and assessment of weapons system and component testing. Shock and vibration environmental testing provides one key piece of evidence for evaluation and qualification of these systems and components in the service environments incurred during a lifetime in the stockpile. LANL’s Test Engineering group continuously pursues research and development in structural dynamics to improve shock and vibration testing capabilities, processes, and analysis techniques to increase the fidelity of service environment recreations in laboratory testing settings. This talk will highlight several ongoing projects to represent these R&D efforts.

42 ENGINEERING↗

Engineering Design of a Linde-BASF Advanced Post-Combustion CO 2 Capture Technology at a Linde Steam Methane Reforming H 2 Plant

Linde carried out an initial engineering design study for a Linde-BASF advanced post combustion CO 2 capture technology to be installed at a commercial-scale steam methane reforming (SMR) hydrogen plant located in the US Gulf Coast. This pre-FEED equivalent study included following: (1) basic design, including specific project scope definition and design basis, (2) basic engineering, including development of process flow diagrams and heat & material balances, (3) inside the battery limit (ISBL) equipment and systems specification, (4) balance of plant outside the battery limit (OSBL) equipment and systems specifications, (5) technology maturation plan, (6) hazard and operability (HAZOP) review, (7) environmental, health and safety (EH&S) assessment and environmental permitting analysis, (8) constructability review, (9) ISBL and OSBL EPC cost estimation, and (10) commercial-scale techno-economic analysis including capital expenditures (CAPEX) and operating expenditures (OPEX) and CO 2 capture cost estimates.

08 HYDROGEN↗

Engineering Study of Svante’s Solid Sorbent Post-Combustion CO 2 Capture Technology at a Linde Steam Methane Reforming H 2 Plant

An initial engineering design study was performed for an advanced post combustion CO 2 capture (PCC) technology to be installed at a commercial-scale steam methane reforming (SMR) hydrogen plant located in the US Gulf Coast. The PCC process integrated the VeloxoTherm™ structured adsorbent technology from Svante for the CO 2 separation and CO 2 compression and purification and balance of plant systems provided by Linde. This pre-FEED equivalent study included following: (1) design basis, (2) basic engineering, including development of process flow diagrams and heat & material balances, (3) inside the battery limit (ISBL) equipment and systems specification, (4) balance of plant outside the battery limit (OSBL) equipment and systems specifications, (5) technology maturation plan, (6) hazard identification (HAZID) review, (7) environmental, health and safety (EH&S) assessment and environmental permitting analysis, (8) constructability review, (9) ISBL and OSBL EPC cost estimation, and (10) commercial-scale techno-economic analysis including capital expenditures (CAPEX) and operating expenditures (OPEX) and CO 2 capture cost estimates.

03 NATURAL GAS↗

Women in Nuclear Security: The United Arab Emirates Story

Historically in the United Arab Emirates, security personnel stationed at nuclear sites were typically men with military or policing backgrounds. Although these groups bring important, transferrable skills and experience to the nuclear security mission, some Emirati stakeholders recognize the increased benefit of a greater diversity of voices and backgrounds within the nuclear security team hierarchy. By recruiting from a wider range of disciplines and encouraging gender diversity, the security team could develop broader insight into security challenges, and a greater variety of perspectives could bring forth more innovative solutions. When aligning a diverse, multinational workforce with a common mission, all members of a security organization must fundamentally change their individual approaches to the work; the entire staff must be on the same page. This can be particularly challenging for some people who find it difficult to transition from a framework of beliefs because of past experiences based on prescriptive, exclusionary, hierarchical thought. Also, national cultural values are learned early, held deeply, and change slowly over the course of generations, and inherent biases rooted in these values can create barriers to the collective progress of a team. Creating a more open, diverse, and transparent culture for the team by accepting a unique, egalitarian, professional nuclear security culture that all members adhere to can be a challenging task for some. In this article, I share my experiences related to professional roadblocks, personal challenges, and lessons learned, particularly those regarding the empowerment of women in science and engineering, while developing and establishing the United Arab Emirates nuclear security program. I also discuss the support (and underrepresentation) of women, including those currently in critical leadership positions, and their careers in nuclear security.

Barakah Nuclear Power Plant↗

BioSecure Digital Twin: Manufacturing Innovation and Cybersecurity Resilience

U.S. national security, prosperity, economy, and well-being require secure, flexible, and resilient Biopharmaceutical Manufacturing. The COVID-19 pandemic reaffirmed that the biomedical production value-chain is vulnerable to disruption and has been under attack from sophisticated nation-state adversaries. Current cyber defenses are inadequate, and the integrity of critical production systems and processes are inherently vulnerable to cyber-attacks, human error, and supply chain disruptions. The following chapter explores how a BioSecure Digital Twin will improve U.S. manufacturing resilience and preparedness to respond to these hazards by significantly improving monitoring, integrity, security, and agility of our manufacturing infrastructure and systems. The BioSecure Digital Twin combines a scalable manufacturing framework with a robust platform for monitoring and control to increase U.S. biopharma manufacturing resilience. Then, the chapter discusses some of the inherent vulnerabilities and challenges at the nexus of health and advanced manufacturing. Next, the chapter highlights that as the Pandemic evolves, we need agility and resilience to overcome significant obstacles. This section highlights an innovative application of Cyber Informed Engineering to developing and deploying a BioSecure Digital Twin to improve the resilience and security of the biopharma industrial supply chain and production processes. Finally, the chapter concludes with a process framework to complement the Digital Twin platform, called the Biopharma (Observe, Orient, Decide, Act) OODA Loop Framework (BOLF), a four-step approach to decision-making outputs from the Digital Twin. The BOLF will help end users leverage twin technology by distilling the available information, focusing the data on context, and rapidly making the best decision while remaining cognizant of changes that can be made as more data becomes available.

99 GENERAL AND MISCELLANEOUS↗

Development of a Turbulent Liquid Spray Atomization Model for Diesel Engine Simulations (Final Technical Report)

This project addresses the systematic lack of predictive capabilities by spray models within engine CFD codes. We develop a new modeling approach to predict the breakup of diesel sprays based on recent literature showing that liquid turbulence plays a fundamental role in spray atomization. A new body of quantitative validation data is also developed as a critical element of the project, leveraging the joint capabilities of Georgia Tech’s high-pressure continuous-flow spray chamber and Argonne National Lab’s near-nozzle x-ray diagnostics at the Advanced Photon Source. This project contributes spatially-resolved measurements of drop size distribution within well-characterized diesel injectors, Spray A and D, from the Engine Combustion Network (ECN) to the engine combustion community for the first time. Utilizing this new body of measurements, we validate and demonstrate a new spray model for diesel sprays, termed the KH-Faeth model, that predicts global and local spray characteristic more accurately than the widely adopted and employed KH model. Predicted drop size distributions are seen to predict measured drops sizes both quantitatively and predictively, with accurate response in droplet size distributions over a wide range of ambient density, injection pressure, and injector nozzle size (Spray A and D) without model tuning. The KH-Faeth model can reduce error in the predicted centerline droplet size profile by up to 80% for ECN Spray D simulations when compared to use of the widely employed KH model.

33 ADVANCED PROPULSION SYSTEMS↗

Perceived Conflicts of Systems Engineering in Early-Stage Research and Development 1

Early Systems Research and Development (ESR&D) is one of the most crucial phases in the product development process. It both blends and blurs the lines between science and engineering, and requires a risk-based, disciplined, and graded approach to effectively manage scope, cost, and complexity of the final product. Many leaders, program managers, and scientists are unwilling to involve systems engineering because of the perception that systems engineering is heavily process oriented, adds unnecessary costs, and should be applied only to mature technologies. The value of systems engineering as applied to ESR&D is unclear to these key individuals. The unfortunate result is that system engineering is not applied to ESR&D. This results in R&D efforts that may have solved the wrong problem, selected the wrong architecture, require technical rework, have difficulty transitioning later maturity levels, and result in higher R&D costs and extended development timelines. This work discusses the difficulty of introducing systems engineering to the research and early development process and their inclination perspectives of researchers, engineers, and managers. The article shall offer potential means to manage the cultural transformation of early adoption of right-sized systems engineering in ESR&D and reverse the attitudinal positions.

42 ENGINEERING↗

Cross-national analysis of food security drivers: comparing results based on the Food Insecurity Experience Scale and Global Food Security Index

Abstract The second UN Sustainable Development Goal establishes food security as a priority for governments, multilateral organizations, and NGOs. These institutions track national-level food security performance with an array of metrics and weigh intervention options considering the leverage of many possible drivers. We studied the relationships between several candidate drivers and two response variables based on prominent measures of national food security: the 2019 Global Food Security Index (GFSI) and the Food Insecurity Experience Scale’s (FIES) estimate of the percentage of a nation’s population experiencing food security or mild food insecurity (FI ). We compared the contributions of explanatory variables in regressions predicting both response variables, and we further tested the stability of our results to changes in explanatory variable selection and in the countries included in regression model training and testing. At the cross-national level, the quantity and quality of a nation’s agricultural land were not predictive of either food security metric. We found mixed evidence that per-capita cereal production, per-hectare cereal yield, an aggregate governance metric, logistics performance, and extent of paid employment work were predictive of national food security. Household spending as measured by per-capita final consumption expenditure (HFCE) was consistently the strongest driver among those studied, alone explaining a median of 92% and 70% of variation (based on out-of-sample R 2 ) in GFSI and FI , respectively. The relative strength of HFCE as a predictor was observed for both response variables and was independent of the countries used for model training, the transformations applied to the explanatory variables prior to model training, and the variable selection technique used to specify multivariate regressions. The results of this cross-national analysis reinforce previous research supportive of a causal mechanism where, in the absence of exceptional local factors, an increase in income drives increase in food security. However, the strength of this effect varies depending on the countries included in regression model fitting. We demonstrate that using multiple response metrics, repeated random sampling of input data, and iterative variable selection facilitates a convergence of evidence approach to analyzing food security drivers.

42 ENGINEERING↗