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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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DOE OSTI2026

Spectral broadening and compression of picosecond pulses in air using a multi-pass cell

We report the spectral broadening and post-compression of picosecond pulses using a multi-pass cell (MPC) operating in air. A 2 m-long bi-concave cavity with 41 reflections and 96.4% transmission was designed and implemented, optimized for the compression of 5.5 ps, 4.5 mJ pulses from a Yb:YAG laser operating at 1030 nm. A 19.3-fold spectral broadening was obtained, increasing the bandwidth from 0.3 nm to 5.8 nm, which enabled pulse compression down to 547 fs with a symmetric temporal profile close to the transform limit. These results demonstrate the feasibility of using open-air MPCs for high-energy picosecond pulse post-compression, without the need for sealed chambers, while preserving high mode quality and transmission. Scaling to pulse higher energy is discussed.

Zaldivar Escola, F. [Univ. of Buenos Aires (Argent↗

DOE OSTI2024

Proposal for a proton-bunch compression experiment at IOTA in the strong space-charge regime

The longitudinal compression of intense proton bunches with strong space-charge force is an essential component of a proton-based muon source for a muon collider. This paper discusses a proton-bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to explore optimal radio frequency (RF) cavity and lattice configurations. IOTA is a compact fixed-energy storage ring that can circulate a 2.5-MeV proton beam with varying beam parameters and lattice configurations. The study will aim to demonstrate a bunch-compression factor of at least 2 in the IOTA ring while examining the impact of intense space-charge effects on the compression process.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Proposal for a Proton-Bunch Compression Experiment at IOTA in the Strong Space-Charge Regime

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2025

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2024

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing

The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the same time lossy compression for scientific data became an important topic for the scientific communities. The teams involved in the JLESC played and are still playing an important role in developing the research, techniques, methods, and technologies making lossy compression for scientific data a key tool for scientists and engineers. Here, in this paper, we present the evolution of lossy compression for scientific data from 2015, describing the situation before the JLESC started, the evolution of this discipline in the past 8 years (until 2023) through the prism of the JLESC collaborations on this topic and some of the remaining open research questions.

Compression for AI↗

DOE OSTI2025

Real-fluid behavior in rapid compression machines: Does it matter?

Rapid compression machines (RCMs) have been extensively used to quantify fuel autoignition chemistry and validate chemical kinetic models at high-pressure conditions. Historically, the analyses of experimental and modeling RCM autoignition data have been conducted based on the adiabatic core hypothesis with ideal gas assumption, where real-fluid behavior has been completely overlooked, though this might be significant at common RCM test conditions. Here, this work presents a first-of-its-kind study that addresses two significant but overlooked questions for autoignition studies within RCMs in the fundamental combustion community: (i) experiment-wise, can unaccounted-for real-fluid behavior in RCMs affect the interpretation and analysis of RCM experimental data? and (ii) simulation-wise, can unaccounted-for real-fluid behavior in RCMs affect RCM autoignition modeling and the validation of chemical kinetic models? To this end, theories for real-fluid isentropic change are newly proposed and derived based on high-order Virial EoS, and are further incorporated into an effective-volume real-fluid autoignition modeling framework newly developed for RCMs. With detailed analyses, the strong real-fluid behavior in representative RCM tests is confirmed, which can greatly influence the interpretation of RCM autoignition experiments, particularly the determination of end-of-compression temperature and evolution of the adiabatic core in the reaction chamber. Furthermore, real-fluid RCM modeling results reveal that considerable error can be introduced into simulating RCM autoignition experiments when following the community-wide accepted effective-volume approach by assuming ideal-gas behavior, which can be as high as 64% in the simulated ignition delay time at compressed pressure of 125 bar and lead to contradictory validation results of chemical kinetic models. Therefore, we recommend the community to adopt frameworks with real-fluid behavior fully accounted for (e.g., the one developed in this study) to analyze and simulate past and future RCM experiments, so as to avoid misinterpretation of RCM autoignition experiments and eliminate the potential errors that can be introduced into the simulation results with the existing RCM modeling frameworks.

High-order Virial equation of state↗

DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Foam-insulated cryo-compressed hydrogen storage vessels for buses

Here, large reductions (40 % vs. compressed gaseous hydrogen vessels and 17 % vs. vacuum insulated cryo-compressed vessels) in hydrogen storage system cost are possible by operating buses with foam-insulated cryo-compressed hydrogen (CcH 2 ) vessels. Detailed thermodynamic analysis reveals that large size and rapid H 2 consumption in buses compensate for the poor performance of foam insulation (∼100 times more conductive than vacuum multilayer insulation), resulting in compact and inexpensive H 2 storage systems with sufficient H 2 capacity for the longest routes (500 km) while maintaining previously identified advantages of CcH 2 systems: increased autonomy, rapid high density refueling, and improved safety, while simultaneously avoiding vacuum insulation stability problems resulting from composite resin outgassing.

Cryo-compressed↗

DOE OSTI2025

A finite-strain rate- and pressure-dependent constitutive framework for analyzing shock compression behavior of cemented tungsten carbides to 100 GPa

In the present study a thermodynamically-consistent finite-strain rate-and-pressure-dependent constitutive framework is implemented to analyze the shock-compression behavior of cemented tungsten carbides to 100 GPa. Central to this framework is the use of logarithmic strain with a set of invariant basis that allow the Cauchy stress tensor to be expressed as a sum of three response terms that are mutually orthogonal, thus permitting a complete separation of the deviatoric and volumetric (pressure) response. An overstress viscoplasticity model that includes strain and strain rate hardening along with thermal softening is used to represent the deviatoric response, while a complete Mie-Grüneisen equation of state (EoS) is used to obtain the pressure response. Using this formulation, the shock-induced compression behavior of cemented tungsten carbide - obtained from planar plate impact experiments using a 30 mm powder gun to peak stresses of up to ~100 GPa - is analyzed to better understand the structure of the measured shock wave profiles and the associated in-material shock quantities. Of particular interest is the evolution of material inelasticity and strength, and temperature in the tungsten carbide samples during the shock compression process.

Cemented tungsten carbide↗

DOE OSTI2025

Compressibility and permeability of particulated non-recyclable municipal solid waste

Biofuels from non-recyclable municipal solid waste (NMSW) stand at the forefront of energy sustainability. However, their widespread adoption is hampered by persistent material handling issues stemming from the variability in NMSW material properties. An enhanced understanding of particulated NMSW properties, particularly compressibility and permeability, is essential to address the feedstock handling challenges and optimize the handling equipment. This study measures the compressibility and gas permeability of five streams of NMSW materials (i.e., rigid plastics, cardboard, thin film, paper, and foam) and their mixtures under different stress conditions. The results highlight the significant variability in compressibility and gas permeability among different streams, as well as the impacts of particle sizes. A semi-empirical model capable of predicting the gas permeability of NMSW mixtures is established and validated. Here, the results also highlight that reduced NMSW particle size helps promote consistency in NMSW feedstock’s physical and mechanical properties, which is favored for handling equipment design in waste-to-energy recovery facilities.

09 BIOMASS FUELS↗

DOE OSTI2026

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Effect of air path heat losses at different locations in vapor compression-based clothes dryer: Quasi-steady modeling and design implications

Clothes drying is among the most power-intensive household end uses, and vapor compression-based clothes dryers offer substantial energy cost savings compared with conventional electric heater dryers. However, parasitic heat losses along the air path, that is, heat loss at the upstream of the drum, inside the drum, and at downstream of the drum, remain rarely quantified, but can strongly affect overall performance according to experiments. Here, this study enhances a vapor compression simulation model by integrating a validated drum model using a dimensionless heat-and-mass-transfer effectiveness correlation derived from 63 drying tests in the literature to form a quasi-steady dryer simulation model. The model is validated against laboratory measurements of a baseline dryer. The impact of heat losses is simulated at three locations and explored through 16 heat loss cases spanning two loads (2 and 5 kg), two airflow rates, and multiple loss distributions. For a 5 kg wet load, eliminating pre-drum and in-drum losses reduces total energy use by up to 34–35% and shortens drying time by 27–38% compared with the baseline. At a 2 kg wet load, introducing post-drum heat loss lowers energy costs by up to 23% and reduces operation time by up to 57% compared with the baseline. The results demonstrate that the impact of heat loss is location dependent. Vapor compression dryers should minimize pre-drum and in-drum losses while potentially exploiting post-drum heat dissipation to enhance the drying rate and energy cost savings.

Dryer↗

DOE OSTI2024

High Compression in Palladium Alloy Metal Foil Pumps

Metal foil pumps (MFPs) are key components in the direct internal recycling inner fuel cycle loop for the recovery of hydrogen isotopes from deuterium-tritium fusion exhaust. Operating under vacuum conditions, they utilize superthermal hydrogen as the feed gas in a process called superpermeation. A notable feature of MFPs is their ability to pump against a pressure gradient. This study examines the compression capabilities of PdAg and PdCu MFPs at low temperatures with a constant feed pressure of 10 Pa. At 75°C, compression ratios exceeding 200 were readily achieved, with downstream pressures exceeding 4500 Pa using PdCu. For both alloys, net fluxes decreased by only ~15% at downstream pressures of 1000 Pa, which offers potential simplifications for the downstream pump train. Performance declined markedly when the temperature was elevated to 200°C. Pump curves were constructed and advocated as the most appropriate manner to assess MFP performance. Separate pressure-driven-permeation experiments at relevant conditions were conducted, providing a direct measurement of the hydrogen dissociation constant $k$ d , which was found to be in good agreement with the previous literature. Further, these measurements were used to predict pump curves and maximum compression ratios by balancing superpermeation with pressure-driven permeation, achieving excellent agreement with experiment. Last, experiments using asymmetric MFPs revealed the detrimental impact that surface impurities have on performance in this system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Delta-Rice: A HDF5 Compression Plugin optimized for Digitized Detector Data

Delta-Rice is an HDF5 (The HDF Group et al., 2020) filter plugin that was developed to compress digitized detector signals recorded by the Nab experiment (Fry et al., 2019), a fundamental neutron physics experiment. This is a two-step process where incoming data is passed through a pre-processing filter and then compressed with Rice coding. A routine for determining the optimal pre-processing filter for a dataset is provided along with an example GPU deployment. When applied to data collected by the Nab data acquisition system, this method produced output files 29% their initial size, and was able to do so with an average read/write throughput in excess of 2 GB/s on a single CPU. Compared to the widely used Gzip compression routine, Delta-Rice reduces the file size by 33% more with over an order of magnitude increase in read/write throughput. Delta-Rice is available on CPU to users through the HDF5 library.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Modulated Thermomechanical Analysis of Compression-Molded High-Density Polyethylene

Thermomechanical analysis (TMA) experiments conducted on high-density polyethylene (HDPE) show both reversible and irreversible dimensional changes. To further explore these reversible and irreversible processes, modulated thermomechanical analysis (MTMA) was used. Before reliable data on compression-molded HDPE was collected, a parameter optimization was performed to obtain a suitable MTMA method. Once a suitable method was obtained, several MTMA experiments were conducted on compression-molded HDPE. This work highlights the steps taken during the MTMA parameter optimization and the results obtained from MTMA experiments conducted on pristine compression-molded HDPE samples.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Membrane Electrode Assembly Manufacturing Automation Technology for the Electrochemical Compression of Hydrogen: Cooperative Research and Development (Final Report)

Electrochemical compression has the possibility to outcompete mechanical compression for hydrogen end- use applications. While HyET has a compressor that can output JO kilograms (kg)/day (fully scalable from home-to-industrial application) at up to 700 bar, the energy demand and reliability require top-quality electrochemical hydrogen compression (EHC) membrane electrode assemblies (MEAs), preferably prepared by cost-effective high-capacity manufacturing. High pressure requires a special MEA design, deviating from typical proton exchange membrane fuel cell (PEMFC) MEAs with adapted catalyst layer substrates, asking for a modified coating process. The National Renewable Energy Laboratory (NREL) will help HyET by developing an automated catalyst coating process fit for EHC MEA manufacturing. In addition, inline quality inspection methods will be developed/selected to improve the MBA quality as it is used for EHC stack assembly. In a joint effort, NREL and HyET will even design an automated manufacturing process for the EHC MEA and approach potential United States (US) suppliers of manufacturing equipment.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

An analysis of alcohol compression ignition strategies on different engine platforms

Strategies that enable ignition of the low cetane alcohol fuels (methanol and ethanol) include intake heating (direct or via hot residual trapping), increased compression ratio (CR), multi-injection strategies, ignition enhancers, and active prechambers. The literature consistently shows alcohol compression ignition (CI) is more efficient than diesel at high loads irrespective of ignition strategy but shows contradictory results at low loads. To understand this, this work combines data from four different engine platforms ranging from a displaced volume of 0.4 to 2.1 L/cyl. using different alcohol CI ignition strategies. Using modeling to support experimental analysis, alcohol-specific efficiency penalties are highlighted to inform alcohol combustion system development. The alcohols’ lower energy density means more fuel must be injected near top dead center to achieve a given load, increasing the relative penalty of sensible/latent heating. Pilot injections help reduce this penalty. Intake heating incurs both a heat transfer penalty and a thermodynamic penalty due to a reduced ratio of specific heats during compression. A strategy that combines elevated CR, large pilot injections, and ignition enhancers can avoid this penalty. Alternatively, a prechamber strategy can achieve this without changing the CR, nor needing ignition enhancers in the fuel. At low loads, diesel burns in a partially premixed mode characterized by high burn rates and low heat losses, reducing alcohol-specific combustion benefits. Alcohol CI on the light-duty platform showed abnormally high heat transfer over diesel compared to other platforms, favoring a more premixed/partially premixed strategy despite a combustion efficiency tradeoff.

33 ADVANCED PROPULSION SYSTEMS↗