Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dl”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations

Abstract. Deep learning (DL) and machine learning (ML) are widely used in hydrological modelling, which plays a critical role in improving the accuracy of hydrological predictions. However, the trade-off between model performance and computational cost has always been a challenge for hydrologists when selecting a suitable model, particularly for probabilistic post-processing with large ensemble members. This study aims to systematically compare the quantile regression forest (QRF) model and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) model as hydrological probabilistic post-processors. Specifically, we evaluate their ability in dealing with biased streamflow simulations driven by three satellite precipitation products across 522 nested sub-basins of the Yalong River basin in China. Model performance is comprehensively assessed using a series of scoring metrics from both probabilistic and deterministic perspectives. Our results show that the QRF model and the CMAL-LSTM model are comparable in terms of probabilistic prediction, and their performances are closely related to the flow accumulation area (FAA) of the sub-basin. The QRF model outperforms the CMAL-LSTM model in most sub-basins with smaller FAA, while the CMAL-LSTM model has an undebatable advantage in sub-basins with FAA larger than 60 000 km2 in the Yalong River basin. In terms of deterministic predictions, the CMAL-LSTM model is preferred, especially when the raw streamflow is poorly simulated and used as input. However, setting aside the differences in model performance, the QRF model with 100-member quantiles demonstrates a noteworthy advantage by exhibiting a 50 % reduction in computation time compared to the CMAL-LSTM model with the same ensemble members in all experiments. As a result, this study provides insights into model selection in hydrological post-processing and the trade-offs between model performance and computational efficiency. The findings highlight the importance of considering the specific application scenario, such as the catchment size and the required accuracy level, when selecting a suitable model for hydrological post-processing.

Geology↗
DOE OSTI2024

Simulation-based inference for parameter estimation of complex watershed simulators

High-resolution, spatially distributed process-based (PB) simulators are widely employed in the study of complex catchment processes and their responses to a changing climate. However, calibrating these PB simulators using observed data remains a significant challenge due to several persistent issues, including the following: (1) intractability stemming from the computational demands and complex responses of simulators, which renders infeasible calculation of the conditional probability of parameters and data, and (2) uncertainty stemming from the choice of simplified representations of complex natural hydrologic processes. Here, we demonstrate how simulation-based inference (SBI) can help address both of these challenges with respect to parameter estimation. SBI uses a learned mapping between the parameter space and observed data to estimate parameters for the generation of calibrated simulations. To demonstrate the potential of SBI in hydrologic modeling, we conduct a set of synthetic experiments to infer two common physical parameters – Manning's coefficient and hydraulic conductivity – using a representation of a snowmelt-dominated catchment in Colorado, USA. We introduce novel deep-learning (DL) components to the SBI approach, including an “emulator” as a surrogate for the PB simulator to rapidly explore parameter responses. We also employ a density-based neural network to represent the joint probability of parameters and data without strong assumptions about its functional form. While addressing intractability, we also show that, if the simulator does not represent the system under study well enough, SBI can yield unreliable parameter estimates. Approaches to adopting the SBI framework for cases in which multiple simulator(s) may be adequate are introduced using a performance-weighting approach. The synthetic experiments presented here test the performance of SBI, using the relationship between the surrogate and PB simulators as a proxy for the real case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Analysis of genomic signatures associated with Variovorax endosphere colonization

This repository contains the analysis code and supporting datasets associated with the study “Genomic signatures in Variovorax enabling colonization of the Populus endosphere.” Beals DG, Carper DL, Hochanadel LH, Jawdy SS, Klingeman DM, Piatkowski BT, Weston DJ, Doktycz MJ, Pelletier DA. 2026. Genomic signatures in Variovorax enabling colonization of the Populus endosphere. mSystems 11:e01605-25. https://doi.org/10.1128/msystems.01605-25 The scripts are organized sequentially (01–07) and document the workflows used for: Sequence-read alignment and feature counting Orthogroup and KEGG Ortholog annotation Count normalization Statistical analysis and aggregation Generation of manuscript figures and tables Repository contents The uncompressed files are the finalized, formatted datasets used to generate the figures and tables reported in the study, including the supplemental CSV files referenced in the manuscript. The accompanying ZIP archive contains the complete codebase and example data_input/ and data_output/ directories illustrating the organization and execution of the analytical workflow. Individual scripts identify the corresponding manuscript analyses and figure panels. Raw sequencing data Raw sequencing reads are available through the NCBI Sequence Read Archive under BioProject accession PRJNA1322484.

Beals, Delaney [ORNL] (ORCID:0000000306274574)↗
DOE OSTI2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗
NASA NTRS1971

Evaluation of some candidate materials for automobile thermal reactors in engine-dynamometer screening tests

Fourteen materials were evaluated in engine screening tests on full-size thermal reactors for automobile engine pollution control systems. Cyclic test-stand engine operation provided 2 hours at 1040 C and a 20-minute air-cool to 70 C each test cycle. Each reactor material was exposed to 83 cycles in 200 hours of engine testing. On the basis of resistance to oxidation and distortion, the best materials included two ferritic iron alloys (Ge 1541 and Armco 18S/R), several commercial oxidation-resistant coatings on AlSl 651 (19-9 DL), and possibly uncoated AISI 310. The best commercial coatings were Cr-Al, Ni-Cr, and a glass ceramic.

Oldrieve, R. E.↗
NASA NTRS1971

Preferential polymerization and adsorption of L-optical isomers of amino acids relative to D-optical isomers on kaolinite templates.

Experiments on the polymerization of the L- and D-optical isomers of aspartic acid and serine using kaolinite as a catalyst showed that the L-optical isomers were polymerized at a much higher rate than the D-optical isomers; racemic (DL-) mixtures were polymerized at an intermediate rate. The peptides formed from the L-monomers were preferentially adsorbed by the clay. In the absence of kaolinite, no significant or consistent difference in the behavior of the L- and D-optical isomers was observed. In experiments on the adsorption of L- and D-phenylalanine by kaolinite, the L-optical isomer was preferentially adsorbed.

Jackson, T. A.↗
NASA NTRS1972

Capillary gas chromatography with two new moderately high temperature phases.

Gas chromatography test results are presented for two new moderately high-temperature phases of Dexsil 400-GC with free hydroxyl end groups (uncapped) and with end groups covered by trimethyl silyl groups (capped). The two Dexsil 400-GC phases were tested for their ability to resolve N-TFA-DL-(+)-2-butyl esters and n-butyl esters, as well as fatty acid methyl esters and hydrocarbon standards. Generally the more polar uncapped phase was superior to the capped phase in all separation comparisons, except for the hydrocarbons.

Pollock, G. E.↗
NASA NTRS1972

Effects of diffusion impairment on O2 and CO2 time courses in pulmonary capillaries.

Simultaneous time courses for O2 and CO2 exchange along the capillary have been calculated for homogeneous lungs, allowing for O2-CO2 interactions, dissolved O2, and chemical reaction rates. As diffusing capacity (Dl) was reduced, the transfer of CO2 and O2 was impaired by similar amounts, in spite of the 20-fold greater diffusing capacity for CO2. The reason why CO2 is affected so much is that the slope of the content against partial pressure is so much greater in blood than tissue for this gas. Because of the shapes of their respective dissociation curves, O2 transfer was most affected at normal ventilation-perfusion ratios, whereas CO2 was most affected at high ratios. Exercise exaggerated the impairment of transfer of both gases.

Wagner, P. D.↗
NASA NTRS1973

The hydrolysis of polyimides

Thermal polymerization of aspartic acid produces a polysuccinimide (I), a chain of aspartoyl residues. An investigation was made of the alkaline hydrolysis of the imide rings of (I) which converts the polyimide to a polypeptide. The alkaline hydrolysis of polyimides can be expected to be kinetically complex due to increasing negative charge generated by carboxylate groups. For this reason, a diimide, phthaloyl-DL-aspartoyl-beta-alanine (IIA) was synthesized for a progressive study of the hydrolysis of polyimides. In addition, this diimide (IIA) can be related to thalidomide and might be expected to exhibit similar reactivity during hydrolysis of the phthalimide ring.

Hoagland, P. D.↗
NASA NTRS1980

Creep-rupture behavior of seven iron-base alloys after long term aging at 760 deg in low pressure hydrogen

Seven candidate iron-base alloys for heater tube application in the Stirling automotive engine were aged for 3500 hours at 760 C in argon and hydrogen. Aging degraded the tensile and creep-rupture properties. The presence of hydrogen during aging caused additional degradiation of the rupture strength in fine grain alloys. Based on current design criteria for the Mod 1 Stirling engine, N-155 and 19-9DL are considered the only alloys in this study with strengths adequate for heater tube service at 760 C.

Witzke, W. R.↗
NASA NTRS1981

Effect of oxide films on hydrogen permeability of candidate Stirling engine heater head tube alloys

The effect of oxide films developed in situ from CO/CO2 doped hydrogen on high pressure hydrogen permeability at 820 C was studied on N-155, A-286, IN 800, 19-9DL, Nitronic 40, HS-188, and IN 718 tubing in a Stirling materials simulator. The hydrogen permeability decreased with increasing dopant levels of CO or CO2 and corresponding decreases in oxide porosity. Minor reactive alloying elements strongly influenced permeability. At high levels of CO or CO2, a liquid oxide formed on alloys with greater than 50 percent Fe. This caused increased permeability. The oxides formed on the inside tube walls were analyzed and their effective permeabilities were calculated.

Schuon, S. R.↗
NASA NTRS1982

Evaluation of candidate stirling engine heater tube alloys at 820 deg and 860 deg C

Seven commercial alloys were evaluated in Stirling simulator materials rigs. Five iron base alloys (N-155, A-286, Incoloy 800, 19-9DL, and 316 stainless steel), one nickel base alloy (Inconel 718), and one cobalt base alloy (HS-188) were tested in the form of thin wall tubing in a diesel fuel fired test rig. Tubes filled with hydrogen or helium at gas pressure of 21.6 MPa and temperatures of 820 and 860 C were endurance tested for 1000 and 535 hours, respectively. Results showed that under these conditions hydrogen permeated rapidly through the tube walls, thus requiring refilling during each five hour cycle. Helium was readily contained, exhibiting no measurable loss by permeation. Helium filled tubes tested at 860 C all exhibited creep-rupture failures within the 535 hour endurance test. Subsequent tensile test evaluation after removal from the rig indicated reduced room temperature ductility for some hydrogen-filled tubes compared to helium-filled tubes, suggesting possible hydrogen embrittlement in these alloys.

Misencik, J. A.↗
NASA NTRS1981

A model for the enantiomeric enrichment of polypeptides on the primitive earth

A potential model is presented for the origin of optical activity in polypeptides on the primitive earth due to enantiomeric enrichment in succeeding polymerization-hydrolysis cycles. The model was developed in experiments with the polymerization of a DL-leucine N-carboxyanhydride mixture with a 31.2% enantiomeric excess of the L isomer with sodium methoxide initiator to yield a polyleucine product which was in turn partially hydrolyzed by acid. The polymerization-hydrolysis was found to produce a net 23.8% increase in the enantiomeric excess of the remaining unhydrolyzed polypeptide (14.2% from the polymerization and 9.6% from the partial hydrolysis). On the basis of these results, it is suggested that a slight excess produced by an appropriate chiral physical process may be enhanced by cycles of stereoselective polymerization and hydrolysis driven by fluctuating wet and dry environmental cycles on the primitive earth.

Blair, N. E.↗
NASA NTRS1982

The radiolysis and racemization of leucine on proton irradiation

D- and L-Leucine have been subjected to 39-55 percent radiolysis using 0.11 MeV protons, both with the proton beam passing through the sample or being absorbed by it and with quenching the sample immediately on completion of irradiation or after a 21-day interval. Racemization was small (1.1-1.7 percent) and comparable in all cases, suggesting that radioracemization and secondary degradative effects were not important factors in the recent unsuccessful attempts to induce optical activity in DL-Leucine by partial radiolysis using 0-11 MeV longitudinally polarized protons.

Bonner, W. A.↗
NASA NTRS1982

Polyamines and plant stress - Activation of putrescine biosynthesis by osmotic shock

The putrescine content of oat leaf cells and protoplasts increases up to 60-fold within 6 hours of exposure to osmotic stress (0.4 to 0.6 molar sorbitol). Barley, corn, wheat, and wild oat leaves show a similar response. Increased arginine decarboxylase activity parallels the rise in putrescine, whereas ornithine decarboxylase remains unchanged. DL-alpha-Difluoromethylarginine, a specific irreversible inhibitor of arginine decarboxylase, prevents the stress-induced rise in increase in arginine decarboxylase activity and putrescine synthesis, indicating the preferential activation of this pathway.

Flores, H. E.↗
NASA NTRS1980

Cast Fe-base cylinder/regenerator housing alloy

The development of an iron-base alloy that can meet the requirements of automotive Stirling engine cylinders and regenerator housings is described. Alloy requirements are as follows: a cast alloy, stress for 5000-hr rupture life of 200 MPa (29 ksi) at 775 C (1427 F), oxidation/corrosion resistance comparable to that of N-155, compatibility with hydrogen, and an alloy cost less than or equal to that of 19-9DL. The preliminary screening and evaluation of ten alloys are described.

Larson, F.↗