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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Estimating Flow-Through Balance Momentum Tares with CFD

This paper describes the process used for estimating flow-through balance momentum tares. The interaction of jet engine exhausts on the BOEINGERA Hybrid Wing Body (HWB) was simulated in the NFAC 40x80 wind tunnel at NASA Ames using a pair of turbine powered simulators (TPS). High-pressure air was passed through a flow-through balance and manifold before being delivered to the TPS units. The force and moment tares that result from the internal shear and pressure distribution were estimated using CFD. Validation of the CFD simulations for these complex internal flows is a challenge, given limited experimental data due to the complications of the internal geometry. Two CFD validation efforts are documented, and comparisons with experimental data from the final model installation are provided.

Balance Momentum Tare↗
NASA NTRS2017

Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis

Closing and balancing Earths global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to in homogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified,MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.

MERRA-2↗
NASA NTRS2019

Observations of Surface Mass Balance on Pine Island Glacier, West Antarctica, and the Effect of Strain History in Fast-Flowing Sections

Surface mass balance (SMB) is the net input of mass on a glacier's upper surface, composed of snow deposition, melt and erosion processes, and is a major contributor to the overall mass balance. Pine Island Glacier (PIG) in West Antarctica has been dynamically imbalanced since the early 1990s, indicating that discharge of solid ice into the oceans exceeds snow deposition. However, observations of the SMB pattern on the fast flowing regions are scarce, and are potentially affected by the firn's strain history. Here, we present new observations from radar-derived stratigraphy and a relatively dense network of firn cores, collected along a ~900 km traverse of PIG. Between 1986 and 2014, the SMB along the traverse was 0.505 m w.e. a−1 on average with a gradient of higher snow deposition in the South-West compared with the North-East of the catchment. We show that along ~80% of the traverse the strain history amounts to a misestimation of SMB below the nominal uncertainty, but can exceed it by a factor 5 in places, making it a significant correction to the SMB estimate locally. We find that the strain correction changes the basin-wide SMB by ~0.7 Gt a−1 and thus forms a negligible (1%) correction to the glacier's total SMB.

ice core↗
NASA NTRSDate not supplied

The Spacecraft Mass Balance as a Diagnostic Tool for Cabin Air Quality

The spacecraft-level mass balance is a powerful tool for diagnosing and decoupling factors influencing cabin air quality, especially with respect to trace contaminant propagation. Successful implementation of this approach relies upon accurate and temporally relevant air quality measurements, which are often challenging to attain for emerging trace contaminants. In addition to the proper interpretation of air quality data trends, a thorough understanding of subsystem-level mass transfer is required to characterize process performance. For many Environmental Control and Life Support System processes, subsystem mass transfer may be predicted based on physicochemical properties and classic unit operation design approaches. Gaps in understanding of process performance should be supplemented with thorough ground testing. A high confidence in the fidelity of one of these two aspects, air quality data or process performance, may help offset uncertainties in the other. At minimum, thresholding assumptions and numerical methods can be imposed to constrain unknown parameters within the physical envelope of the situation at hand. Finally, the complexity of cabin-wide integrated mass balances may be reduced by implementing a phenomenological approach towards subsystem discretization.

Cabin Air-quality↗
NASA NTRS2021

Reanalysis Surface Mass Balance of the Greenland Ice Sheet along K-transect (2000-2014)

Accurate estimates of surface mass balance over the Greenland ice sheet (GrIS) would contribute to understanding the cause of recent changes and would help to better estimate the future contribution of the GrIS to sea-level rise. Given the limitations of in-situ measurement, modeling, and remote sensing, it is critical to explore the opportunity to merge the available data to better characterize the spatial and temporal variation of the GrIS surface mass balance (SMB). This work utilizes a particle batch smoother data assimilation technique that yields SMB estimates that benefit from the snow model Crocus and a 16-day albedo product derived from satellite remote sensing data. Comparison of the results against in-situ SMB measurements shows that the assimilation of the albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB by 51% and reduces bias by 95%.

Greenland Ice Sheet↗
NASA NTRSDate not supplied

Evaluation of a Traditional Regression Model Term Selection Process for Balance Calibration Data Sets

Key elements of a traditional regression model term selection process for the analysis of wind tunnel strain-gage balance calibration data are discussed. The traditional process is sometimes applied when regression models of the gage outputs are needed and an analyst does not have access to a term selection algorithm. In principle, the traditional process identifies supported regression model terms of a gage output by combining an analyst's subject- matter knowledge with a visual examination of selected plots of the calibration loads. Twelve empirical rules are listed that may be used to select regression model terms. Data from the manual calibration of a force balance is used to illustrate the application of the traditional term selection process. The data example shows that the traditional process can become very complex. Its successful application highly depends on an analyst's experience and skills. Therefore, it is suggested to replace the traditional term selection process with an automated term selection algorithm. Then, objective metrics are systematically applied during the term selection that make the identification of the regression model more repeatable and less dependent on an analyst's personal skills.

strain-gage balance↗
NASA NTRS2021

Mass Balance of the Antarctic Ice Sheet 1992–2016: Reconciling Results from GRACE Gravimetry With ICESat, ERS1/2 and Envisat Altimetry

GRACE and ICESat Antarctic mass-balance differences are resolved utilizing their dependencies on corrections for changes in mass and volume of the same underlying mantle material forced by ice-loading changes. Modeled gravimetry corrections are 5.22 times altimetry corrections over East Antarctica (EA) and 4.51 times over West Antarctica (WA), with inferred mantle densities 4.75 and 4.11 g/cu. cm. Derived sensitivities (Sg, Sa) to bedrock motion enable calculation of motion (δB0) needed to equalize GRACE and ICESat mass changes during 2003–08. For EA, δB0 is −2.2 mm/a subsidence with mass matching at 150 Gt/a, inland WA is −3.5 mm/a at 66 Gt/a, and coastal WA is only −0.35 mm/a at −95 Gt/a. WA subsidence is attributed to low mantle viscosity with faster responses to post-LGM deglaciation and to ice growth during Holocene grounding-line readvance. EA subsidence is attributed to Holocene dynamic thickening. With Antarctic Peninsula loss of −26 Gt/a, the Antarctic total gain is 95 ± 25 Gt/a during 2003–08, compared to 144 ± 61 Gt/a from ERS1/2 during 1992–2001. Beginning in 2009, large increases in coastal WA dynamic losses overcame long-term EA and inland WA gains bringing Antarctica close to balance at −12 ± 64 Gt/a by 2012–16.

Antarctic glaciology↗
NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations

Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.

Urban Air Mobility↗
NASA NTRS2023

Towards an Indian Land Data Assimilation System (ILDAS): A Coupled Hydrologic-Hydraulic System for Water Balance Assessments

Effective management of water resources requires reliable estimates of land surface states and fluxes, including water balance components. But most land surface models run in uncoupled mode and do not produce river discharge at catchment scales to be useful for water resources management applications. Such integrated systems are also rare over India where hydrometeorological extremes have wreaked havoc on the economy and people. So, an Indian Land Data Assimilation System (ILDAS) with a coupled land surface and a hydrodynamic model has been developed and driven by multiple meteorological forcings (0.1°, daily) to estimate land surface states, channel discharge, and floodplain inundation. ILDAS benefits from an integrated framework as well as the largest suite of observation records collected over India and has been used to produce a reanalysis product for 1981–2021 using four forcing datasets, namely, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), ECMWF’s ERA-5, and Indian Meteorological Department (IMD) gridded precipitation. We assessed the uncertainty and bias in these precipitation datasets and validated all major components of the terrestrial water balance, i.e., surface runoff, soil moisture, terrestrial water storage anomalies, evapotranspiration, and streamflow, against a combination of satellite and in situ observation datasets. Our assessment shows that ILDAS can represent the hydrological processes reasonably well over the Indian landmass with IMD precipitation showing the best relative performance. Evaluation against ESA-CCI soil moisture shows that MERRA-2 based estimates outperform the others, whereas ERA-5 performs best in simulating evapotranspiration when evaluated against MODIS ET. Evaluations against observed records show that CHIRPS-based estimates have the highest performance in reconstructing surface runoff and streamflow. Once operational, this system will be useful for supporting transboundary water management decision making in the region.

Indian Land Data Assimilation System (ILDAS)↗
NASA NTRS2023

Assessing the Performance of the South American Land Data Assimilation System Version 2 (SALDAS-2) Energy Balance across Diverse Biomes

Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance.

modeling↗
NASA NTRSDate not supplied

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗
DOE OSTI2023

Modeling a Gas-Cooled Microreactor Balance of Plant for the Virtual Test Bed

High Temperature Gas-cooled Reactors (HTGRs) are one of the technology considered for microreactor designs because of their high performance and technological maturity. Several designs are being developed. These microreactor cores are connected to power conversion system (PCS) through a heat exchanger. For transient analysis, the feedback of the PCS or of the primary loop can be important, therefore, it is necessary to develop robust models for the balance of plant that can be coupled to a core model. In this work, a balance of plant model using the MOOSE Thermal Hydraulics module (THM) is presented and demonstrated for startup and load-follow transients. This model can be seamlessly coupled with any MOOSE-based multi-physics core model using the MOOSE multi-app approach.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1945

Hinge Moments of Sealed-Internal-Balance Arrangements for Control Surfaces I : Theoretical Investigation

The results of a theoretical analysis of the hinge-moment characteristics of various sealed-internal-balance arrangements for control surfaces are presented. The analysis considered overhands sealed to various types of wing structure by flexible seals spanning gaps of various widths or sealed to the wing structure by a flexible system of linked plates. Leakage was not considered; the seal was assumed to extend the full spanwise length of the control surface. The effect of the developed width of the flexible seal and of the geometry of the structure to which the seal was anchored was investigated, as well as the effect of the gap width that is sealed. The results of the investigation indicated that the most nearly linear control-surface hinge-moment characteristics can probably be obtained from a flexible seal over a narrow gap (about 0.1 of the overhang chord), which is so installed that the motion of the seal is restricted to a region behind the point of attachment of the seal to the wing structure. Control-surface hinge moments that tend to be high at large deflections and low or overbalanced at small deflections will result if a very narrow seal is used.

CONTROL SURFACES, BALANCED - OVERHANG↗
DOE OSTI2020

Balancing Ionic and Electronic Conduction for High‐Performance Organic Electrochemical Transistors

Abstract Conjugated polymers that support mixed (electronic and ionic) conduction are in demand for applications spanning from bioelectronics to energy harvesting and storage. To design polymer mixed conductors for high‐performance electrochemical devices, relationships between the chemical structure, charge transport, and morphology must be established. A polymer series bearing the same p‐type conjugated backbone with increasing percentage of hydrophilic, ethylene glycol side chains is synthesized, and their performance in aqueous electrolyte gated organic electrochemical transistors (OECTs) is studied. By using device physics principles and electrochemical analyses, a direct relationship is found between the OECT performance and the balanced mixed conduction. While hydrophilic side chains are required to facilitate ion transport—thus enabling OECT operation—swelling of the polymer is not de facto beneficial for balancing mixed conduction. It is shown that heterogeneous water uptake disrupts the electronic conductivity of the film, leading to OECTs with lower transconductance and slower response times. The combination of in situ electrochemical and structural techniques shown here contributes to the establishment of the structure–property relations necessary to improve the performance of polymer mixed conductors and subsequently of OECTs.

Savva, Achilleas↗
DOE OSTI2024

Pathway Evolution Through a Bottlenecking-Debottlenecking Strategy and Machine Learning-Aided Flux Balancing

The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L -1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Achieving Balanced Crystallization Kinetics of Donor and Acceptor by Sequential-Blade Coated Double Bulk Heterojunction Organic Solar Cells

Sequential deposition has great potential to achieve high performance in organic solar cells due to the resulting well-controlled vertical phase separation. In this work, double bulk heterojunction organic solar cells are fabricated by sequential-blade cast in ambient conditions. Probed by the in situ grazing incidence X-ray diffraction and in situ UV–vis absorption measurements, the seq-blade system exhibits a different tendency from each of the binary films during the film formation process. Due to the extensive aggregation of FOIC, the binary PBDB-T:FOIC film displays a strong and large phase separation, resulting in low current density (J sc) and unsatisfactory power conversion efficiency. In the seq-blade cast system, the bottom layer PBDB-T:IT-M produces many crystal nuclei for the top layer PBDB-T:FOIC, so the PBDB-T molecules are able to crystallize easily and quickly. Balanced crystallization kinetics between polymer and small molecule and an ideal percolation network in the film are observed. In addition, the balanced crystallization kinetics are favorable toward realizing lower recombination loss through charge transport processes.

14 SOLAR ENERGY↗
DOE OSTI2025

Efficient Quantum Gibbs Samplers with Kubo–Martin–Schwinger Detailed Balance Condition

Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial thermostat in classical Monte Carlo or molecular dynamics methods, rather than being treated as an approximation to weakly coupled system-bath unitary dynamics. Recently, Chen, Kastoryano, and Gilyén (arXiv:2311.09207) introduced the first efficiently implementable Lindbladian satisfying the Kubo–Martin–Schwinger (KMS) detailed balance condition, which ensures that the Gibbs state is a fixed point of the dynamics and is applicable to non-commuting Hamiltonians. This Gibbs sampler uses a continuously parameterized set of jump operators, and the energy resolution required for implementing each jump operator depends only logarithmically on the precision and the mixing time. In this work, we build upon the structural characterization of KMS detailed balanced Lindbladians by Fagnola and Umanità, and develop a family of efficient quantum Gibbs samplers using a finite set of jump operators (the number can be as few as one), akin to the classical Markov chain-based sampling algorithm. Compared to the existing works, our quantum Gibbs samplers have a comparable quantum simulation cost but with greater design flexibility and a much simpler implementation and error analysis. Moreover, it encompasses the construction of Chen, Kastoryano, and Gilyén as a special instance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗