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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

PLA recycling by hydrolysis at high temperature

In this work the process of PLA hydrolysis at high temperature was studied, in order to evaluate the possibility of chemical recycling of this polymer bio-based. In particular, the possibility to obtain the monomer of lactic acid from PLA degradation was investigated. The results of some preliminary tests, performed in a laboratory batch reactor at high temperature, are presented: the experimental results show that the complete degradation of PLA can be obtained in relatively low reaction times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

CMS readiness for multi-core workload scheduling

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

CST R9120-B 30x60 Media Pretreatment and Digestion Standard Development to Support Tank Closure Cesium Removal 1A (TCCR-1A) Operations

In support of continued operations of Savannah River Remediation’s (SRR) ion exchange process to remove radioactive cesium from Savannah River Site (SRS) dissolved saltcake, referred to as the Tank Closure Cesium Removal 1A process (TCCR-1A; containing the second set of at-tank ion exchange columns), SRNL was tasked with: 1) validating the field protocol planned for pretreating the crystalline silicotitanate (CST) ion exchange media to be used in the columns, 2) preparing CST media for use in in-tank batch contact testing, and 3) developing a digestion standard to verify complete CST dissolution prior to characterization following each in-tank batch contact test. A procedure (SRNL L29 Manual, ITS-0229) was developed previously in support of the TCCR Demonstration (which contained the first set of ion exchange columns) based on evaluations of a different CST production lot with a larger particle size range to document the protocol for pretreating CST utilizing conditions similar to what will be performed in the field.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Microbial Influence on the Mobility of +3 Actinides from a Salt-Based Nuclear Waste Repository

Biologically enhanced transport of radionuclides is one of several processes that can affect the performance of a nuclear waste repository. In this work, several microbial isolates from the Waste Isolation Pilot Plant (WIPP) were tested for their influence on the concentration of neodymium, as an analog for +3 actinides, in simple sodium chloride solutions and in anoxic WIPP brines. Batch sorption experiments were carried out over a period of 4–5 weeks. In many cases, the effect on neodymium in solution was immediate and extensive and assumed to be due to surface complexation. However, over time, the continued loss of Nd from the solution was more likely due to biologically induced precipitation and/or mineralization and possible entrapment in extracellular polymeric substances. The results showed no correlation between organism type and the extent of its influence on neodymium in solution. However, a correlation was observed between different test matrices (simple NaCl versus high-magnesium brine versus high-NaCl brine). Further experiments were conducted to test these matrix effects, and the results showed a significant effect of magnesium concentration on the ability of microorganisms to remove Nd from solution. Possible mechanisms include cation competition and the alteration of cell surface structures. This suggests that the aqueous chemistry of the WIPP environs could play a larger role in the final disposition of +3 actinides than the microbiology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Sorption testing and generalized composite surface complexation models for determining uranium sorption parameters at a proposed in-situ recovery site

Solid-phase iron concentrations and generalized composite surface complexation models were used to evaluate procedures in determining uranium sorption on oxidized aquifer material at a proposed U in situ recovery (ISR) site. At the proposed Dewey Burdock ISR site in South Dakota, USA, oxidized aquifer material occurs downgradient of the U ore zones. Solid-phase Fe concentrations did not explain our batch sorption test results,though total extracted Fe appeared to be positively correlated with overall measured U sorption. Batch sorption test results were used to develop generalized composite surface complexation models that incorporated the full genericsorption potential of each sample, without detailed mineralogiccharacterization. The resultant models provide U sorption parameters (site densities and equilibrium constants) for reactive transport modeling. The generalized composite surface complexation sorption models were calibrated to batch sorption data from three oxidized core samples using inverse modeling, and gave larger sorption parameters than just U sorption on the measured solidphase Fe. These larger sorption parameters can significantly influence reactive transport modeling, potentially increasing U attenuation. Because of the limited number of calibration points, inverse modeling required the reduction of estimated parameters by fixing two parameters. The best-fit models used fixed values for equilibrium constants, with the sorption site densities being estimated by the inversion process. While these inverse routines did provide best-fit sorption parameters, local minima and correlated parameters might require further evaluation. Despite our limited number of proxy samples, the procedures presented provide a valuable methodology to consider for sites where metal sorption parameters are required. Furthermore, these sorption parameters can be used in reactive transport modeling to assess downgradient metal attenuation, especially when no other calibration data are available, such as at proposed U ISR sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bioinspired mineralizing microenvironments generated by liquid-liquid phase coexistence

Biominerals such as bones, teeth and shells exhibit improved mechanical properties and intricate morphologies not seen in nonbiologically-produced minerals of ostensibly the same composition. These remarkable properties of biogenic minerals are thought to arise due to precise local control over the mineral deposition process, including organic and inorganic inclusions. Understanding how Biology controls the local reaction environment during formation of these materials to control their composition, structure, and properties is a grand challenge that promises to enable new routes to high-performance materials. This project developed multi-compartment bioinspired microreactors as artificial mineralizing vesicles, and used them to understand and control formation of inorganic/organic composite solid materials. A major emphasis was on developing all-aqueous emulsions in which each droplet was a structured microreactor with two or more adjacent phases. This approach provided local control over reaction environment including availability of inclusions such as polypeptides and metal ions, while being sufficiently simple to produce large populations of essentially identical multiphase reactor droplets simultaneously within a batch. Organic/inorganic composite materials could be produced with very high organic content that stabilized the inorganic portions as amorphous materials (e.g., amorphous calcium carbonate) by preventing the typical conversion to more thermodynamically crystalline forms (e.g., calcite). These stabilized amorphous composites could be stored indefinitely and converted to crystalline forms later by removal of the organic inclusions via, for example, heating. Compositional gradients in the organic and inorganic components were embedded during synthesis due to the evolution of the reaction microenvironment, and despite the complexity of this process it occurred similarly across the population of reactive droplets and was hence encoded into the population of resulting composite particles. The approach developed here allows pre-structuring of reactive microenvironments to control the spatiotemporal reaction environment, which is an important step towards rational design and on-demand production of complex functional materials with desired composition, optical properties, and mechanical response.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Determination of biogas generation potential as a renewable energy source from supermarket wastes

Highlights: • Disposal of supermarket wastes in landfills may contribute to environmental pollution. • High methane yields can be obtained from supermarket wastes by anaerobic co-digestion. • Fruit and vegetable wastes or dairy products wastes could individually be handled by a two-stage anaerobic process. • Buffering capacity, trace metal and C/N ratio are essential for digestion of supermarket wastes. - Abstract: Fruit, vegetable, flower waste (FVFW), dairy products waste (DPW), meat waste (MW) and sugar waste (SW) obtained from a supermarket chain were anaerobically digested, in order to recover methane as a source of renewable energy. Batch mesophilic anaerobic reactors were run at total solids (TS) ratios of 5%, 8% and 10%. The highest methane yield of 0.44 L CH{sub 4}/g VS{sub added} was obtained from anaerobic digestion of wastes (FVFW + DPW + MW + SW) at 10% TS, with 66.4% of methane (CH{sub 4}) composition in biogas. Anaerobic digestion of mixed wastes at 5% and 8% TS provided slightly lower methane yields of 0.41 and 0.40 L CH{sub 4}/g VS{sub added}, respectively. When the wastes were digested alone without co-substrate addition, the highest methane yield of 0.40 L CH{sub 4}/g VS{sub added} was obtained from FVFW at 5% TS. Generally, although the volatile solids (VS) conversion percentages seemed low during the experiments, higher methane yields could be obtained from anaerobic digestion of supermarket wastes. A suitable carbon/nitrogen (C/N) ratio, proper adjustment of the buffering capacity and the addition of essential trace nutrients (such as Ni) could improve VS conversion and biogas production yields significantly.

09 BIOMASS FUELS↗
DOE OSTI2013

Advanced Insulation for High Performance Cost-Effective Wall, Roof, and Foundation Systems Final Report

The objective of this project was to explore and potentially develop high performing insulation with increased R/inch and low impact on climate change that would help design highly insulating building envelope systems with more durable performance and lower overall system cost than envelopes with equivalent performance made with materials available today. The proposed technical approach relied on insulation foams with nanoscale pores (about 100 nm in size) in which heat transfer will be decreased. Through the development of new foaming methods, of new polymer formulations and new analytical techniques, and by advancing the understanding of how cells nucleate, expand and stabilize at the nanoscale, Dow successfully invented and developed methods to produce foams with 100 nm cells and 80% porosity by batch foaming at the laboratory scale. Measurements of the gas conductivity on small nanofoam specimen confirmed quantitatively the benefit of nanoscale cells (Knudsen effect) to increase insulation value, which was the key technical hypotheses of the program. In order to bring this technology closer to a viable semi-continuous/continuous process, the project team modified an existing continuous extrusion foaming process as well as designed and built a custom system to produce 6" x 6" foam panels. Dow demonstrated for the first time that nanofoams can be produced in a both processes. However, due to technical delays, foam characteristics achieved so far fall short of the 100 nm target set for optimal insulation foams. In parallel with the technology development, effort was directed to the determination of most promising applications for nanocellular insulation foam. Voice of Customer (VOC) exercise confirmed that demand for high-R value product will rise due to building code increased requirements in the near future, but that acceptance for novel products by building industry may be slow. Partnerships with green builders, initial launches in smaller markets (e.g. EIFS), and efforts to drive cost down will help acceptance in residential and commercial retrofit and new construction.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)

Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.

Peterson, Chariya↗
DOE OSTI2026

Bio-based oxalic acid production in Issatchenkia orientalis enables sustainable rare earth recovery

The growing demand for rare earth elements (REEs) in clean energy and high-tech industries underscores the need for sustainable recovery methods and a reliable supply of processing chemicals. Here, we establish a microbial platform using the acid-tolerant yeast Issatchenkia orientalis SD108 to produce bio-oxalic acid for REE recovery. By introducing an oxaloacetate cleavage pathway and applying metabolic engineering, the engineered strain produces 39.53 g·L -1 oxalic acid at pH 4.0 in fed-batch fermentation. The crude fermentation broth, used without purification, efficiently precipitates over 99% neodymium (Nd), 99% dysprosium (Dy), and 98% lanthanum (La) from individual REE chloride solutions. Recovery from a low-grade ore leachate achieves over 99% total recovery. X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) confirm that REE oxalates precipitated with bio-oxalic acid closely resemble those obtained using commercial oxalic acid. Techno-economic analysis (TEA) and life cycle assessment (LCA) further demonstrate that bio-oxalic acid can be produced at a competitive price of $1.79·kg -1 while reducing carbon intensity (CI) by 112% to 63.5% with and without electricity displacement, respectively, relative to the fossil-based benchmark. These results highlight bio-oxalic acid as a green, economically viable alternative to synthetic oxalate for sustainable REE recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Pilot Testing of a Modular Oxygen Production System Using Oxygen Binding Adsorbents (Final Report)

In this project, RTI and Air Liquide have focused on the development of innovative oxygen separation materials and technologies based on reversibly binding of oxygen to enable smaller and cheaper air separations. In alignment with that object the team has had multiple achievements to advance the technology including: Synthesized and characterized novel M-CoSalen (RTIO2Sorb-1) material which showed a dynamic oxygen adsorption capacity in excess of 1wt%. Developed synthesis routes for RTIO2Sorb-1 with commercially relevant techniques and produced batches of 0.25kg and over 4 kg of total synthesis. Synthesized and characterized extrudate forms of the RTIO2Sorb-1 with relevant crush strength and maintained dynamic oxygen adsorption capacity in near 1wt%. Developed techniques for forming structured beds in fiber shapes with conventional materials. Developed a model for O 2 sorption processes to analyze various bed configurations and cycle parameters. Studied classic O 2 solid sorbents reported in the literature to learn oxygen binding mechanisms. Design a 10 kg/day O 2 VPSA pilot system with 2 or 4-bed operation. Completed a techno-economic analysis based on the experimental results and modeling. The overall objective of the project was to design, fabricate, and test a modular O 2 production system and perform a techno-economic analysis (TEA) after testing to determine the cost-benefit of the advanced modular air separation system. The goals of this technology development project were to achieve a bed-size factor (BSF) of less than 600 lb-adsorbent/TPD O 2 (ton/day O 2 ) (as compared with the state-of-the-art BSF of 850), and O 2 -purity greater than 95% at a cost that is projected to be equivalent or lower than the current state of the art (SOTA), commercially available large-scale cryogenic air separation systems. To achieve these goals and objective, the project team executed on (1) oxygen binding adsorbent optimization and scale up, (2) adsorbent material formation process studies to form the adsorbent material into structured beds for rapid pressure swing adsorption (PSA) cycles with low pressure drop, fast mass transfer, and low attrition, (3) cycle development studies to optimize the PSA process, and (4) develop simulation tools for rapid cycle modeling and numerical evaluation/optimization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics

Liquid chromatography–high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a “primary” feature list is used as a template for matching compounds in “target” feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution’s in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

NASA PERT time II

Program Evaulation and Review Technique (PERT) is disciplined management technique involving computer processing. NASA PERT Time 11 gives project manager insight into current and future project development and forewarns of potential problems. Program utilizes modular technique. Module is "fragnet"; once aspects of project are described in terms of fragnets, control network is automatically generated. Program is written in FORTRAN IV and OS Assembler for batch execution and has been implemented on IBM 370.

Bainbridge, R. C.↗
NASA NTRS2006

ASPEN Version 3.0

The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and random access memories.

Rabideau, Gregg↗
NASA NTRS2006

Tool for Analysis and Reduction of Scientific Data

The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN as a whole (up to version 2.0) has been summarized, and selected aspects of ASPEN have been discussed in several previous NASA Tech Briefs articles. Restated briefly, ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and randomaccess memories. Domain-specific reasoning modules (e.g., modules for determining orbits for spacecraft) can easily be plugged into ASPEN 3.0. Improvements over other, similar software that have been incorporated into ASPEN 3.0 include a provision for more expressive time-line values, new parsing capabilities afforded by an ASPEN language based on Extensible Markup Language, improved search capabilities, and improved interfaces to other, utility-type software (notably including MATLAB).

James, Mark↗
DOE OSTI2020

Implementation of Ion Exchange Processes for Carbon Dioxide Mineralization Using Industrial Waste Streams

Sequestration of CO 2 within stable mineral carbonates (e.g., CaCO 3 ) represents an attractive emission reduction strategy because it offers a leakage-free alternative to geological storage of CO 2 in an environmentally benign form. However, the pH of aqueous streams equilibrated with gaseous streams containing CO 2 (pH < 4) are typically lower than that which is required for carbonate precipitation (pH > 8). Traditionally, alkalinity is provided by a stoichiometric reagent (e.g., NaOH) which renders these processes environmentally hazardous and economically unfeasible. This work investigates the use of regenerable ion-exchange materials to induce alkalinity in CO 2 -saturated aqueous solutions such that the pH shift required for mineralization occurs without the need for stoichiometric reagents. Na + -H + exchange isotherms (at [H + ] = 10 −8 –10 −1 M) and rates were measured for 13X and 4A zeolites and TP-207 and TP-260 organic exchange resins in batch equilibrium and fixed-bed exchange experiments, respectively. At solutions equilibrated with CO 2 at 1.0 atm (pH = 3.9), H + exchange capacities for the materials were similar (1.7–2.4 mmol H + /g material) and resulted in pH increases from 3.9 to greater than 8.0. Multi-component mixtures using Ca 2+ and Mg 2+ cations (at 10 −3 –10 −1 M) in CO 2 -saturated water were used to probe competitive ion exchange. The presence of divalent cations in solution inhibited H + exchange, reducing capacities to as low as 0.2 mmol H + /g for both resins and zeolites. Dynamic H + exchange capacities in fixed-bed ion exchange columns were similar to equilibrium values for resins (∼1.5 mmol/g) and zeolites (∼0.8 mmol/g) using inlet solutions that were equilibrated with gaseous streams of CO 2 at 1.0 atm. However, exchange kinetics were limited by intraparticle diffusion as indicated by the increased rate parameters with increasing inlet flow rates (20–160 cm 3 min −1 ). Experimental calcite precipitation from mixing the alkaline CO 3 2− -rich water solution obtained from the ion-exchange column with a simulated liquid waste stream solution achieved thermodynamic maximum yields. The results from these studies indicate that ion exchange processes can be used as an alternative to the addition of stoichiometric bases to induce alkalinity for the precipitation of CaCO 3 , thereby opening a pathway toward sustainable and economic mineralization processes.

42 ENGINEERING↗
DOE OSTI2019

LP-BNN: Ultra-low-Latency BNN Inference with Layer Parallelism

High inference latency seriously limits the deployment of DNNs in real-time domains such as autonomous driving, robotic control, and many others. To address this emerging challenge, researchers have proposed approximate DNNs with reduced precision, e.g., Binarized Neural Networks (BNNs). While BNNs can be built to have little loss in accuracy, latency reduction still has much room for improvement. In this paper, we propose a single-FPGA-based BNN accelerator that achieves microsecond-level ultra-low-latency inference of ImageNet, LP- BNN. We obtain this performance via several design optimizations. First, we optimize the network structure by removing Batch Normalization (BN) functions which leads to significant latency in BNNs without any loss on accuracy. Second, we propose a parameterized architecture which is based on layer parallelism and supports nearly perfect load balancing for various types of BNNs. Third, we fuse all the convolution layers and the first fully connected layer. We process them in parallel through fine- grained inter-layer pipelining. With our proposed accelerator, the inference of binarized AlexNet, VGGNet, and ResNet are completed within 21.5µs, 355µs, and 67.8µs respectively, with no loss in accuracy as compared with other BNN implementations.

Geng, Tong↗
DOE OSTI2020

RLScheduler: An Automated HPC Batch Job Scheduler Using Reinforcement Learning

Today’s high-performance computing (HPC) platforms are still dominated by batch jobs. Accordingly, effective batch job scheduling is crucial to obtain high system efficiency. Existing HPC batch job schedulers typically leverage heuristic priority functions to prioritize and schedule jobs. But, once configured and deployed by the experts, such priority functions can hardly adapt to the changes of job loads, optimization goals, or system settings, potentially leading to degraded system efficiency when changes occur. To address this fundamental issue, we present RLScheduler, an automated HPC batch job scheduler built on reinforcement learning. RLScheduler relies on minimal manual interventions or expert knowledge, but can learn high-quality scheduling policies via its own continuous ‘trial and error’. We introduce a new kernel-based neural network structure and trajectory filtering mechanism in RLScheduler to improve and stabilize the learning process. Through extensive evaluations, we confirm that RLScheduler can learn high-quality scheduling policies towards various workloads and various optimization goals with relatively low computation cost. Moreover, we show that the learned models perform stably even when applied to unseen workloads, making them practical for production use.

Zhang, Di↗