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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Factor analytic reduction of the carotid-cardiac baroreflex parameters

An accepted method for measuring the responsiveness of the carotid-cardiac baroreflex to arterial pressure changes is to artificially stimulate the baroreceptors in the neck. This is accomplished by using a pressurized neck cuff which constricts and distends the carotid artery and subsequently stimulates the baroreceptors. Nine physiological responses to this type of stimulation are quantified and used as indicators of the baroreflex. Thirty male humans between the ages 27 and 46 underwent the carotid-cardiac baroreflex test. The data for the nine response parameters were analyzed by principle component factor analysis. The results of this analysis indicated that 93 percent of the total variance across all nine parameters could be explained in four dimensions. Examination of the factor loadings following an orthogonal rotation of the principle components indicated four well defined dimensions. The first two dimensions reflected location points for R-R interval and carotid distending pressure respectively. The third dimension was composed of measures reflecting the gain of the reflex. The fourth dimension was the ratio of the resting R-R interval to R-R interval during simulated hypertension. The data suggests that the analysis of all nine baroreflex parameters is redundant.

Ludwig, David A.↗
NASA NTRS2016

Origins of Line Defects in Self-Reacting Friction Stir Welds and Their Impact on Weld Quality

Friction stir welding (FSWing) is a solid state joining technique which reduces the occurrence of typical defects formed in fusion welds, especially of highly alloyed metals. Although the process is robust for aluminum alloys, occasional reductions in the strength of FSWs have been observed. Shortly after the NASA-MSFC implemented a variation of FSW called self-reacting (SR), low strength properties were observed. At that time, this reduction in strength was attributed to a line defect. At that time, the limited data suggested that the line defect was related to the accumulation of native oxides that form on the weld lands and faying surfaces. Through a series of improved cleaning methods, tool redesign, and process parameter modifications, the reduction in the strength of the SR-FSWs was eliminated. As more data has been collected, the occasional reduction in the strength of SR-FSW still occurs. These occasional reductions indicate a need to reexamine the underlying causes. This study builds off a series of self reacting (SR)-FSWs that were made in 3 different thickness panels of AA2219 (0.95, 1.27 and 1.56 cm) at 2 different weld pitches. A bead on plate SR-FSW was also made in the 1.56 cm thick panel to understand the contribution of the former faying surfaces. Copper tracer studies were used to understand the flow lines associated with the weld tool used. The quality of the SR-FSWs was evaluated from tensile testing at room temperature. Reductions in the tensile strength were observed in some weldments, primarily at higher weld pitch or tool rotations. This study explores possible correlations between line defects and the reduction of strength in SR-FSWs. Results from this study will assist in a better understand of the mechanisms responsible for reduced tensile strength and provide methodology for minimizing their occurrence.

Schneider, Judy↗
NASA NTRS1986

Effects of noise on modal parameters identified by the Eigensystem Realization Algorithm

The basic concept of the Eigensystem Realization Algorithm for modal parameter identification and model reduction is extended to minimize the distortion of the identified parameters caused by noise. The mathematical foundation for the properties of accuracy indicators, such as the singular values of the data matrix and modal amplitude coherence, is provided, based on knowledge of the noise characteristics. These indicators quantitatively discriminate noise from system information and are used to reduce the realized system model to a better approximation of the true model. Monte Carlo Simulations are included to support the analytical studies.

Juang, J.-N.↗
NASA NTRS1986

Effects of noise on ERA-identified modal parameters

The basic concept of the Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction is extended to minimize the distortion of the identified parameters caused by noise. The mathematical foundation for the properties of accuracy indicators such as the singular values of the data matrix and modal amplitude coherence is provided based on knowledge of the noise characteristics. These indicators quantitatively discriminate noise from system information and are used to reduce the realized system model to a better approximation of the true model. Monte Carlo simulations are included to support the analytical studies.

Juang, J.-N.↗
NASA NTRS1985

Shock associated noise of inverted-profile coannular jets. I - Experiments

The reduction of shock-associated noise in inverted-velocity-profile coannular jets is quantified and explained by conducting extensive optical and acoustic measurements for a suitable range of outer-stream and inner-stream presure-ratio combinations, and by interpreting the measured noise results with the aid of new theoretical models. It is shown that the shock noise from the outer stream is virtually eliminated when the inner stream is operated at a Mach number just above unity, regardless of all the other jet operating parameters. Furthermore, this reduction can be achieved at inverted-velocity-profile as well as normal-velocity-profile conditions.

Tanna, H. K.↗
DOE OSTI2023

Enhancing the activity of Fe-N-C oxygen reduction reaction electrocatalysts by high-throughput exploration of synthesis parameters

Here, the most active class of platinum group metal-free (PGM-free) oxygen reduction reaction (ORR) electrocatalysts in acidic electrolytes are those synthesized by heat treatment of iron, carbon, nitrogen precursors (Fe-N-C). Due to the large number of possible precursor compounds, a small fraction of the synthesis variable space has been explored. Correlation of synthesis variables with Fe speciation and ORR activity has been limited. In this work, an automation platform and a multi-port ball-milling were utilized to evaluate the effects of synthesis variables, such as identity of iron precursor, iron loading, and carbon and nitrogen sources on the ORR activity of iron -nitrogen-carbon catalysts in acidic electrolyte. The ORR activity is correlated with catalyst Fe speciation determined using Fe K-edge X-ray absorption spectroscopy (XAFS).

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Kβ X-ray Emission Spectra Analysis Using Bayesian Optimization

The Kβ X-ray emission spectrum of 3 d transition metals is rich with electronic and structural information due to strong exchange interactions with the valence shell of the metal, and has become crucial for understanding their spin and oxidation states. The spectrum is commonly treated using crystal-field multiplet theory, a semi-empirical theory that uses tunable parameters to control the strength of the effects present in X-ray emission spectroscopy (XES). However, determining the experimental values of these parameters remains a challenge. We present a methodology that applies Bayesian optimization to crystal-field multiplet theory to determine parameter values. The algorithm is tested on the X-ray emission spectra of a collection of Mn, Co, and Ni oxides. We are able to find optimal values for the four most impactful parameters: Slater−Condon reduction factors F dd , F pd , and G pd , and crystal field splitting 10 Dq . The algorithm produces significantly improved accuracy compared to current analysis methods, and probes interparameter dependencies by modeling the error landscape. This advancement enhances XES analysis by offering an approach of obtaining quantitative electronic structural information on 3 d transition metal valence shells, facilitating applications across various scientific fields.

Bayesian optimization↗
DOE OSTI2025

Rate expressions and kinetic parameters for metal ferrites in relation to applications of fossil fuel conversion to hydrogen: Part 1 of 2

Here, the goal of the present work was to provide the necessary reaction emulation information to enable detailed process simulation of a chemical looping H 2 production system from fossil fuels using CaFe 2 O 4 . This specifically pertained to the necessary kinetic data, reaction model development, and model rate parameters required for reaction emulation in both reducing and oxidizing environments. A logical methodology was defined, which included discretization of the reaction network, establishing a core model for reaction emulation that could be adapted based on the system phenomena, and development of a rate parameter regression tool designed around the core model. An extensive array of data sets was acquired by which parametric regressions were performed. The work presented and tabulated a comprehensive set of rate parameters for the reduction and oxidation reactions of CaFe 2 O 4 and descendent phases of Ca 2 Fe 2 O 5 , FeO, Fe 3 O 4 , Fe, and CaO to emulate reaction behavior in a looping-based process environment. This included direct reduction using CH 4 , H 2 , and CO, and direct oxidation reactions with steam, CO 2 and O 2 . Dynamic equilibrium was quantified for reactions that could utilize H 2 O and CO 2 as soft oxidants to re-saturate lattice oxygen in the depleted structure/phases. The kinetics associated with the oxidative mechanisms with the soft oxidants were quantified and compared to those of the reducing counterparts. The analysis provided critical insight to emulate reactions for a process that seeks to use natural gas (NG) or other fossil fuels as a direct reductant for the end goal of H 2 production.

calcium ferrite oxygen carriers↗
DOE OSTI2020

Life-cycle energy use and greenhouse gas emissions of palm fatty acid distillate derived renewable diesel

This study aims to quantify life-cycle fossil energy use and greenhouse gas (GHG) emissions for palm fatty acid distillate (PFAD) derived renewable diesel (RD) taking into consideration different feedstock classifications that are applicable to PFAD (residue, byproduct, or coproduct), and incorporating updated data for key processes. Under the three classifications, the PFAD to RD pathway was modeled using the Greenhouse gases, Regulated Emissions, and Energy Use in Technologies (GREET®) model. PFAD-derived RD could reduce fossil energy consumption by 77%–88%, relative to petroleum diesel. GHG emissions are very sensitive to PFAD classification and coproduct handling methods. Considering the production of palm oil and PFAD and economic value, we maintain that PFAD should be treated as a byproduct in palm oil refineries. With this treatment, PFAD-derived RD could achieve 84% GHG emissions reductions, compared to the emissions of petroleum diesel. We also employed a substitution method to address the substitution of PFAD by other materials in the marketplace. Compared to coproduct allocation results, we found substituting PFAD by tallow, soy oil, barley, and canola oil results in lower GHG emissions. Due to high induced land-use change emissions associated with palm farming, if PFAD is treated as a coproduct with refined palm oil, PFAD-derived RD may not deliver GHG reductions. A sensitivity analysis identified key parameters such as palm fruit yield, oil extraction efficiency in oil mills, and energy use intensity for RD production affects LCA results significantly; future efforts to improve these parameters could result in further GHG reductions.

09 BIOMASS FUELS↗
DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗
DOE OSTI2020

Bi aliovalent substitution in Li 7 La 3 Zr 2 O 12 garnets: Structural and ionic conductivity effects

We report on the synthesis of cubic-phase garnet-type solid-state electrolytes based on Bi-doped Li 7 La 3 Zr 2 O 12 (LLZO). Bi aliovalent substitution of Zr in LLZO utilizing the Pechini processing method is employed to synthesize Li 7-x La 3 Zr 2-x Bi x O 12 compounds. A strong dependence of the ionic conductivity on Bi content is observed, and under our synthesis and sintering conditions, a >100-fold increase over the un-doped sample is observed for x=0.75. Cubic-phase Li 6 La 3 Zr 1 BiO 12 compounds are generated upon annealing in air in the temperature range 650 °C-900 °C. In contrast, in the absence of Bi, the cubic garnet phase of Li 7 La 3 Zr 2 O 12 is not formed below 700 °C and a transformation to the tetragonal phase is observed at similar to 900 °C for this un-doped compound. The role of Bi in lowering the formation temperature of the garnet cubic phase and in the ionic conductivity improvements is investigated in this work. We ascribe the effect of Bi-doping on ionic conductivity increments to changes in Li + -site occupancy and lattice parameters and the reduction in the formation temperature for the cubic-phase formation to rate enhancements of the solid-state reaction. To identify the site occupancy of Bi in the garnet structure, we employ synchrotron extended x-ray absorption fine structure spectroscopy. Our results indicate that Bi additions occupy the Zr-type sites exclusively, to within the accuracy of the measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effects of 63 MeV proton irradiation on the performance of MWIR InGaAs/InAsSb nBn photodetectors

An investigation into the effects of 63 MeV proton irradiation on high-sensitivity mid-wave infrared InGaAs/InAsSb nBn devices is performed. Three different structures with various absorber region doping profiles are irradiated and characterized to assess their impact on performance degradation. Minority carrier lifetime is measured using time-resolved photoluminescence and lifetime damage factors are assessed. The majority carrier concentration is determined via capacitance–voltage measurements and dopant introduction rates are calculated. An analysis of dark current density is performed using these material parameters, revealing a reduction in mobility with proton fluence and the emergence of a proton-induced trap energy level. Quantum efficiency is calculated at each proton fluence, and quantum efficiency damage factors show that the graded doping structure exhibits the least reduction of quantum efficiency with dose, attributed to its effective mobility enhancement. Conclusively, detector sensitivity, assessed via shot-noise limited noise-equivalent irradiance, shows that the graded doping structure is the least susceptible to high energy proton irradiation-induced performance degradation.

Physics↗
DOE OSTI2020

Tailoring Surface Roughness Using Additive Manufacturing to Improve Internal Cooling

Abstract Surface roughness present on internal cooling channels produced with additive manufacturing has been previously shown to augment heat transfer and pressure loss to levels similar to traditionally cast turbulators. Given the ability of the surface roughness to improve the cooling performance of small cooling channels, the question arises on whether there is an optimal combination of random roughness features to maximize internal cooling performance. To investigate this question, test coupons with different surface roughness morphologies and magnitudes were manufactured by manipulating the parameters in the laser powder bed fusion additive manufacturing process. The coupons were tested to characterize the friction factor and Nusselt number of the cooling channels over a range of Reynolds numbers. Results showed that certain roughness combinations outperformed others, increasing the internal cooling performance of the channels. Additionally, manipulation of the performance using the process parameters allowed for reductions in build time, which could be useful for controlling component cost.

Engineering↗
DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗
DOE OSTI2024

The effects of exercise training interventions on depression in hemodialysis patients

Purpose Depression considerably influences the clinical outcomes, treatment compliance, quality of life, and mortality of hemodialysis patients. Exercise plays a beneficial role in depressive patients, but its quantitative effects remain elusive. This study aimed to summarize the effects of exercise training on depression in patients with end-stage renal disease undergoing hemodialysis. Methods The PUBMED, EMBASE, and Cochrane Library databases were systematically searched from inception to April 2023 to identify published articles reporting the effect of exercise training on the depression level of patients with End-Stage Renal Disease undergoing hemodialysis. Data were extracted from the included studies using predefined data fields by two independent researchers. The Cochrane Handbook for Systematic Reviews of Interventions and Joanna Briggs Institute Critical Appraisal Checklist for Quasi-Experimental Studies were employed for quality evaluation. Results A total of 22 studies enrolling 1,059 patients who participated in exercise interventions were included. Hemodialysis patients exhibited superior outcomes with intradialytic exercise (SMD = −0.80, 95% CI: −1.10 to −0.49) and lower levels of depression following aerobic exercise (SMD = −0.93, 95%CI: −1.32 to −0.55) compared to combined exercise (c − 0.85, 95% CI: −1.29 to −0.41) and resistance exercise (SMD = −0.40, 95%CI: −0.96 to 0.17). Regarding exercise duration, patients manifested lower depression levels when engaging in exercise activities for a duration exceeding 6 months (SMD = −0.92, 95% CI: −1.67 to −0.17). Concerning the duration of a single exercise session, the most significant improvement was noted when the exercise duration exceeded 60 min (SMD = −1.47, 95% CI: −1.87 to −1.06). Conclusion Our study determined that exercise can alleviate depression symptoms in hemodialysis patients. This study established the varying impacts of different exercise parameters on the reduction of depression levels in hemodialysis patients and is anticipated to lay a theoretical reference for clinicians and nurses to devise tailored exercise strategies for interventions in patients with depression. Systematic review registration https://www.crd.york.ac.uk/prospero/ , This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database, with registration number CRD42023434181.

Yu, Huihui↗
NASA NTRS1976

Laboratory calibration of AAFE radiometer/scatterometer (RADSCAT)

A brief description of the electrical and mechanical instrument configuration, followed by an extensive discussion of laboratory tests and results are contained herein. This information is required to provide parameters for data reduction, and a basis for analysis of the measurement errors in data taken with this instrument.

Schroeder, L. C.↗
NASA NTRS1977

A model of the 1.6 GHz scatterometer

The performance was studied of the 1.6 GHz airborne scatterometer system which is used as one of several Johnson Space Center (JSC) microwave remote sensors to detect moisture content of soil. The system is analyzed with respect to its antenna pattern and coupling, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principle and the sensitivity of the system, as well as data handling are also described. The finite cross-polarized gains of all four 1.6 GHz scatterometer antennae are found to have profound influence on the cross-polarized backscattered signal returns. If these signals are not analyzed properly, large errors could result in the estimate of the cross-polarized coefficient. It is also found necessary to make corrections to the variations of the aircraft parameters during data reduction in order to minimize the error in the coefficient estimate. Finally, a few recommendations are made to improve the overall performance of the scatterometer system.

Wang, J. R.↗