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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application of Box-Behnken design in optimizing product properties of supercritical methanol co -liquefaction of rice straw and linear low-density polyethylene

We report co-processing of plastic and biomass wastes to produce high-quality fuel has been attracting considerable interest in energy recovery. This work employed Box-Behnken Design (BBD) to optimize yield and properties of oil from supercritical methanol (scMeOH) co-liquefaction of rice straw (RS) and linear low-density polyethylene (LLDPE). Three independent variables of reaction temperature (270, 300, and 330°C), holding time (60, 90, and 120 mins), and RS/LLDPE mass ratio (0.15, 0.50, and 0.85) were selected for experiments. A maximum oil yield of 34.17 wt% was achieved at 303°C, 96 mins, and RS/LLDPE ratio of 0.59 according to BBD. Temperature and RS/LLDPE ratio dominated the oil yield and synergistic effects during co-liquefaction, whereas time was an insignificant factor. Optimum oil from co-liquefaction contained substantial hydrocarbons content of 32.91% compared to that from single RS-derived oil of 7.77%. Solid product obtained at the optimum condition could be used as solid fuel, due to its relatively high HHV of 43.08 MJ/kg compared to the other solid fuels (13.90–32.14 MJ/kg). This work provides a deep understanding of the co-processing of solid biomass and plastic wastes.

09 BIOMASS FUELS↗
DOE OSTI2026

Stochastic Thermo-Hydro Modeling and Neural Network Surrogate Development for Thermal Resource Assessment of the Galleries-to-Calories Geobattery

The Galleries-to-Calories Geobattery concept explores the use of abandoned coal mine workings for large-scale thermal energy transport and storage. The system involves injecting waste heat from a supercomputing facility into flooded mine galleries, where groundwater flow can store and transport thermal energy for potential recovery in downgradient district heating and cooling applications. To evaluate the feasibility and performance of the Geobattery under geological and operational uncertainty, we developed a suite of stochastic thermo-hydrological (TH) simulations using Monte Carlo sampling of key uncertain parameters (e.g., permeability, porosity, thermal conductivity, specific heat capacity) and operating conditions (e.g., injection rate, injection temperature). Results identified injection rate and temperature as the most influential parameters governing thermal front propagation, while the geometry of the room-and-pillar structure played a critical role in directing the extent and orientation of thermal advancement. Optimal combinations of material properties for maximizing heat recovery were also determined. To address the high computational cost of coupled-process stochastic modeling, we trained a neural network surrogate model on 24,000 physics-based realizations, achieving an R² > 0.99 and MAE < 0.1 for temperature predictions at monitoring locations. This surrogate enabled an additional 100,000 realizations for global sensitivity analysis and probabilistic thermal resource assessment. The integrated stochastic physics–surrogate modeling framework offers a computationally efficient tool for quantifying uncertainty, identifying key drivers, and informing early-stage design decisions for Geobattery systems.

15 - GEOTHERMAL ENERGY↗
NASA NTRSDate not supplied

Recovery from Missed Thrust During Gateway's NRHO Insertion Using Auxiliary Propulsion

Results are presented by which a high thrust reaction control system (RCS) can be used to complete insertion of the Gateway into a Near Rectilinear Halo Orbit (NRHO) in the event of a missed thrust event (MTE).Recovery solutions are presented in terms of the response time afforded, the ∆v required, and the NRHO insertion delay relative to the reference trajectory. Results are presented for methodologies that maintain the reference trajectory NRHO insertion epoch as well as those that optimize this insertion epoch in order to buy down recovery costs and increase the robustness of solutions. This analysis presents solutions which, in the event of an MTE during NRHO insertion, enable RCS recoveries that require under 20 m/s ∆v and less than four days of NRHO insertion delay.

mission design↗
DOE OSTI2021

VirION2: a short- and long-read sequencing and informatics workflow to study the genomic diversity of viruses in nature

Microbes play fundamental roles in shaping natural ecosystem properties and functions, but do so under constraints imposed by their viral predators. However, studying viruses in nature can be challenging due to low biomass and the lack of universal gene markers. Though metagenomic short-read sequencing has greatly improved our virus ecology toolkit—and revealed many critical ecosystem roles for viruses—microdiverse populations and fine-scale genomic traits are missed. Some of these microdiverse populations are abundant and the missed regions may be of interest for identifying selection pressures that underpin evolutionary constraints associated with hosts and environments. Though long-read sequencing promises complete virus genomes on single reads, it currently suffers from high DNA requirements and sequencing errors that limit accurate gene prediction. Here we introduce VirION2, an integrated short- and long-read metagenomic wet-lab and informatics pipeline that updates our previous method (VirION) to further enhance the utility of long-read viral metagenomics. Using a viral mock community, we first optimized laboratory protocols (polymerase choice, DNA shearing size, PCR cycling) to enable 76% longer reads (now median length of 6,965 bp) from 100-fold less input DNA (now 1 nanogram). Using a virome from a natural seawater sample, we compared viromes generated with VirION2 against other library preparation options (unamplified, original VirION, and short-read), and optimized downstream informatics for improved long-read error correction and assembly. VirION2 assemblies combined with short-read based data (‘enhanced’ viromes), provided significant improvements over VirION libraries in the recovery of longer and more complete viral genomes, and our optimized error-correction strategy using long- and short-read data achieved 99.97% accuracy. In the seawater virome, VirION2 assemblies captured 5,161 viral populations (including all of the virus populations observed in the other assemblies), 30% of which were uniquely assembled through inclusion of long-reads, and 22% of the top 10% most abundant virus populations derived from assembly of long-reads. Viral populations unique to VirION2 assemblies had significantly higher microdiversity means, which may explain why short-read virome approaches failed to capture them. These findings suggest the VirION2 sample prep and workflow can help researchers better investigate the virosphere, even from challenging low-biomass samples. Our new protocols are available to the research community on protocols.io as a ‘living document’ to facilitate dissemination of updates to keep pace with the rapid evolution of long-read sequencing technology.

Long-reads↗
DOE OSTI2026

Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)

Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.

Sudan, Kavish [University of Louisville, KY]↗
DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗
NASA NTRSDate not supplied

Voxel Based Three-Dimensional Topology Optimization of Heat Exchanger Fins

Increasing interest in novel aircraft propulsion systems and potential for unwanted heat generation, or capture and reuse of waste heat, may require increasingly lightweight and high performing heat exchangers. Advances in manufacturing technologies have shown potential to create complex designs, but design tools need more flexibility. This study utilizes genetic algorithm-driven topology optimization to develop high performance heat exchanger fins for critical applications such as aerospace. The solid domain is generated using voxel representation where a voxel value of 1 indicates the solid domain and a voxel value of 0 refers to the fluid domain. The use of voxel representation somewhat matches the digitization of a model that is required to fabricate using additive manufacturing, and also allows for a highly unconstrained geometry. To test the topology optimization approach, a three-dimensional(3D)baseline offset strip fin geometry in steady laminar flow(Reynolds number = 215)with conjugate heat transfer(simultaneous solution of solid and fluid temperature fields)is optimized. New designs are generated using the genetic algorithm (GA) and sent to evaluation by the CFD software OpenFOAM; then the GA sorts and selects the reproduction pool for the following generation. This process is repeated for 60 generations. The study also investigates the effect off in material on the performance of the GA and the resulting designs. The results show that the optimal designs have overall performance improvement of 18% relative to the baseline. Additionally, a fin constructed of a lower conductivity material (such as an Inconel super alloy that might be necessary for waste heat recovery applications)results in lower overall performance improvement (11%)and optimal designs with higher pressure drop relative to their baseline, and relative to optimal designs produced using higher conductivity materials.

3D Optimization↗
DOE OSTI2025

Extraction of high-purity medium-chain-length polyhydroxyalkanoates via combined mechanical treatment and mild oxidation

Polyhydroxyalkanoates (PHAs) are a class of polyester polymers of microbial origin and considered biodegradable alternatives to conventional plastics. To make PHAs cost-competitive with synthetic plastics, their production cost, including extraction cost, should be significantly reduced. Herein, this study aimed to develop an effective extraction method based on combined mechanical disruption and chemical treatment for the recovery of high-purity medium-chain-length PHAs (mcl-PHAs) at a lower cost. mcl-PHAs-accumulating Pseudomonas strains were used for PHA extraction via high-pressure homogenization (HPH) coupled with surfactant treatment and mild alkaline hydrogen peroxide oxidation. The mechanical-chemical method was found to have strong synergy for PHA extraction while minimizing PHA depolymerization. The optimized condition resulted in nearly 90 % mcl-PHA recovery with high purity (>91 %). The extracted high-purity PHAs exhibited thermal and mechanical properties suitable for downstream applications entailing flexible and elastomeric materials.

42 ENGINEERING↗
DOE OSTI2021

Chemical looping air separation with Sr 0.8 Ca0.2Fe 0.9 Co 0.1 O 3-δ perovskite sorbent: Packed bed modeling, verification, and optimization

Chemical looping air separation (CLAS) represents a promising approach for efficient O 2 production from the air. This present study aims at optimizing the absorber/desorber operations and the separation process with extensive experimental validation. Specifically, a one-dimensional packed bed model was developed to investigate the CLAS operation with a Sr 0.8 Ca 0.2 Fe 0.9 Co 0.1 O 3-δ perovskite sorbent. The redox thermodynamics of perovskite sorbent was measured by TGA and then incorporated into a linear driving force model to describe the O 2 absorption and desorption rates. Both 4-step and 5-step air separation cycle configurations, with various cyclic structures, were performed in a subpilot-scale packed bed. The model predicted O2 purity and productivity were consistent with experimental results, supporting its accuracy and applicability. Parametric analysis and multi-objective optimization were further carried out to assess the performance of CLAS. Both O 2 purity and recovery increased monotonically with the cycle time, airflow rate, steam flow rate, and absorption pressure. Meanwhile, optimal O 2 productivity and power consumption can only be achieved by specific combinations of these parameters. The optimized results showed that CLAS can be highly competitive when compared to conventional pressure swing adsorption (PSA) or cryogenic distillation. The 5-step cycle configuration achieved a minimum power consumption of 118 kW·h for producing 1 ton O 2 with ≥ 95% purity. The maximum O 2 productivity reached 0.0932 g O2 /(g sorbent ·h) with 390 kW·h/ton O 2 of energy consumption (95% pure). The optimization results also indicate that CLAS can potentially be more efficient than cryogenic distillation even when the required O 2 purity is above 99%.

42 ENGINEERING↗
DOE OSTI2023

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗
DOE OSTI2024

Regulation of NMDAR activation efficiency by environmental factors and subunit composition

NMDA receptors (NMDAR) convert the major excitatory neurotransmitter glutamate into a synaptic signal. A key question is how efficiently the ion channel opens in response to the rapid exposure to presynaptic glutamate release. Here, we applied glutamate to single channel outside-out patches and measured the successes of channel openings and the latency to first opening to assay the activation efficiency of NMDARs under different physiological conditions and with different human subunit compositions. For GluN1/GluN2A receptors, we find that various factors, including intracellular ATP and GTP, can enhance the efficiency of activation presumably via the intracellular C-terminal domain. Notably, an energy-based internal solution or increasing the time between applications to increase recovery time improved efficiency. However, even under these optimized conditions and with a 1-s glutamate application, there remained around 10–15% inefficiency. Channel activation became more inefficient with brief synaptic-like pulses of glutamate at 2 ms. Of the different NMDAR subunit compositions, GluN2B-containing NMDARs showed the lowest success rate and longest latency to first openings, highlighting that they display the most distinct activation mechanism. In contrast, putative triheteromeric GluN1/GluN2A/GluN2B receptors showed high activation efficiency. Despite the low open probability, NMDARs containing either GluN2C or GluN2D subunits displayed high activation efficiency, nearly comparable with that for GluN2A-containing receptors. These results highlight that activation efficiency in NMDARs can be regulated by environmental surroundings and varies across different subunits.

He, Miaomiao (ORCID:0000000203179136)↗
DOE OSTI2024

Optimization of electroporation method and promoter evaluation for type-1 methanotroph, Methylotuvimicrobium alcaliphilum

Methanotrophic bacteria are promising hosts for methane bioconversion to biochemicals or bioproducts. However, due to limitations associated with long genetic manipulation timelines and, lack of choice in genetic tools required for strain engineering, methanotrophs are currently not employed for bioconversion technologies. In this study, a rapid and reproducible electroporation protocol is developed for type 1 methanotroph, Methylotuvimicrobium alcaliphilum using common laboratory solutions, analyzing optimal electroshock voltages and post-shock cell recovery time. Successful reproducibility of the developed method was achieved when different replicative plasmids were assessed on lab adapted vs. wild-type M. alcaliphilum strains (DASS vs. DSM19304). Overall, a ∼ 3-fold decrease in time is reported with use of electroporation protocol developed here, compared to conjugation, which is the traditionally employed approach. Additionally, an inducible (3-methyl benzoate) and a constitutive (sucrose phosphate synthase) promoter is characterized for their strength in driving gene expression.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Computational-experimental pressure distributions on a transonic, low-aspect-ratio wing

A generic, transonic, supercritical, low aspect-ratio wing was tested at design incidence of 5 deg at Mach numbers from 0.25 to 0.96. Oil-flow studies at the design Mach number of 0.85 showed local-flow separation, which, in retrospect, might have been avoided. At Mach 0.82 with unseparated flow, the surface-flow angles were less than 10 deg. Predictions with the FLO22 transonic potential code are good. Lift interference is strong without tunnel-wall suction. Evidence from this study shows that wings that are optimized for mild shock waves and pressure-recovery gradients generally have small, three-dimensional flow at conditions for unseparated flow.

Keener, E. R.↗
NASA NTRS1985

Pressure-distribution measurements on a transonic low-aspect ratio wing

Experimental surface pressure distributions and oil flow photographs are presented for a 0.90 m semispan model of NASA/Lockheed Wing C, a generic transonic, supercritical, low aspect ratio, highly 3-dimensional configuration. This wing was tested at the design angle of attack of 5 deg over a Mach number range from 0.25 to 0.96, and a Reynolds number range from 3.4 x 1,000,000 to 10 x 1,000,000. Pressures were measured with both the tunnel floor and ceiling suction slots open for most of the tests but taped closed for some tests to simulate solid walls. A comparison is made with the measured pressures from a small model in high Reynolds number facility and with predicted pressures using two three dimesional, transonic full potential flow wing codes: design code FLO22 (nonconservative) and TWING code (conservative). At the given design condition, a small region of flow separation occurred. At a Mach number of 0.82 the flow was unseparated and the surface flow angles were less than 10 deg, indicating that the boundary layer flow was not 3-D. Evidence indicate that wings that are optimized for mild shock waves and mild pressure recovery gradients generally have small 3-D boundary layer flow at design conditions for unseparated flow.

Keener, E. R.↗
NASA NTRS2010

Analyses of the Integration of Carbon Dioxide Removal Assembly, Compressor, Accumulator and Sabatier Carbon Dioxide Reduction Assembly

A tool has been developed by the Sabatier Team for analyzing/optimizing CO2 removal assembly, CO2 compressor size, its operation logic, water generation from Sabatier, utilization of CO2 from crew metabolic output, and Hz from oxygen generation assembly. Tests had been conducted using CDRA/Simulation compressor set-up at MSFC in 2003. Analysis of test data has validated CO2 desorption rate profile, CO2 compressor performance, CO2 recovery and CO2 vacuum vent in CDRA desorption. Optimizing the compressor size and compressor operation logic for an integrated closed air revitalization system Is being conducted by the Sabatier Team.

Jeng, Frank F.↗
NASA NTRS2010

An Interactive Preliminary Design System of High Speed Forebody and Inlet Flows

This paper demonstrates a simulation-based aerodynamic design process of high speed inlet. A genetic algorithm is integrated into the design process to facilitate the single objective optimization. The objective function is the total pressure recovery and is obtained by using a PNS solver for its computing efficiency. The system developed uses existing software of geometry definition, mesh generation and CFD analysis. The process which produces increasingly desirable design in each genetic evolution over many generations is automatically carried out. A generic two-dimensional inlet is created as a showcase to demonstrate the capabilities of this tool. A parameterized study of geometric shape and size of the showcase is also presented.

Liou, May-Fun↗