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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 811 records · Page 45

OC6 Phase I: Investigating the underprediction of low-frequency hydrodynamic loads and responses of a floating wind turbine

Phase I of the OC6 project is focused on examining why offshore wind design tools underpredict the response (loads/motion) of the OC5-DeepCwind semisubmersible at its surge and pitch natural frequencies. Previous investigations showed that the underprediction was primarily related to nonlinear hydrodynamic loading, so two new validation campaigns were performed to separately examine the different hydrodynamic load components. In this paper, we validate a variety of tools against this new test data, focusing on the ability to accurately model the low-frequency loads on a semisubmersible floater when held fixed under wave excitation and when forced to oscillate in the surge direction. However, it is observed that models providing better load predictions in these two scenarios do not necessarily produce a more accurate motion response in a moored configuration.

17 WIND ENERGY↗

Comprehensive Studies on Hot Compaction and Vibration-Assisted Compaction Tests of Aluminum Powder

Abstract Aluminum powder compaction was studied using both test and simulation. Cold compaction, hot compaction, and vibration-assisted (cold) compaction tests were conducted to achieve different density ratios. First, the hot compaction test (at 300 °C, compression pressure 140 MPa) improved about 6% compared with cold compaction under the same compression pressure. Second, although the relative density ratio does not obviously improve at a vibration-assisted (cold) compaction, the strength of the specimens made under vibration loading is much better than those of cold compaction. Additionally, finite element models with well-calibrated Drucker–Prager Cap (DPC) material constitutive model were built in abaqus/standard to simulate the powder compaction process. The results of the finite element model have very good correlations with test results up to the tested range, and this finite element model further predicts the loading conditions needed to achieve the higher density ratios. Two exponential equations of the predicted density ratio were obtained by combining the test data and the simulation results. A new analytical solution was developed to predict the axial pressure versus the density ratio for the powder compaction according to DPC material model. The results between the analytical solution and the simulation model have a very good match.

Engineering↗

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

behind-the-meter↗

Radon emanation rate measurements using liquid scintillation counting

This article describes a radon emanation measurement technique using liquid scintillator counting. A model for radon loading and transport is described, along with its calibration. Detector background and blank have been studied and quantified. The Minimal detectable activity has been determined for the counting setup using a toy Monte Carlo simulation. Here, the measurement technique is validated using a butyl rubber sample previously used for cross-calibration between different radon counting facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Building thermal model development of typical house in U.S. for virtual storage control of aggregated building loads based on limited available information

A building thermal model is an essential component for achieving optimal control of a building’s heating, ventilation, and air conditioning (HVAC). A self-learning grey-box model has been developed by implementing data-driven techniques and utilizing limited available information about the building. In previous research, detailed foreknown knowledge/information, e.g. physical and thermal properties of building materials, as well as sufficient number of observation points, e.g. indoor temperature sensors in different zones, are available for making the decision of model structure and parameters searching range easier. The availability of measured data and a narrowed searching range of model parameters, e.g. resistance and capacity for each wall, made the adopted algorithms quickly achieve near optimal values, which closely approximate the actual heat transfer of a building. Meanwhile, the details of pre-processing of the key inputs were seldom explained. Compared to the previous research, in this study, the available information is assumed to be limited which can fill the requirement for large scale virtual storage control of real residential community in near future, where it may be impractically or over time-consuming to acquire the detailed information for each single house. The developed model is validated by comparing the results to measured data in a recently-built home typical of the southeastern United States.

Cui, Borui↗

Occupant Preference-Aware Load Scheduling for Resilient Communities

The load scheduling of resilient communities in the islanded mode is subject to many uncertainties such as weather forecast errors and occupant behavior stochasticity. To date, it remains unclear how occupant preferences affect the effectiveness of the load scheduling of resilient communities. This paper proposes an occupant thermal preference-aware load scheduler for resilient communities operating in the islanded mode. First, key resilience indicators are selected to quantify its impacts on the load scheduling of a resilient community. A deterministic model predictive control-based load scheduling framework is adopted as the baseline. Then, a chance-constrained controller is proposed to address the occupant-induced uncertainty in room temperature setpoints. Finally, the chance-constrained controller is compared with the deterministic controller on a virtual community testbed based on a real-world net-zero energy community in Florida, U.S. Results have shown that the proposed chance-constrained controller performs better in terms of serving occupants’ thermal preference and the required battery sizes compared to the deterministic controller with the presence of the assumed stochastic occupant behavior. This work indicates that it is necessary to consider the stochasticity of the occupant behavior when designing optimal load schedulers for resilient communities.

Wang, Jing↗

Impact of heating and cooling loads on battery energy storage system sizing in extreme cold climates

Efficient operation of battery energy storage systems requires that battery temperature remains within a specific range. Current techno-economic models neglect the parasitic loads heating and cooling operations have on these devices, assuming they operate at constant temperature. In this work, these effects are investigated considering the optimal sizing of battery energy storage systems when deployed in cold environments. Here, a peak shaving application is presented as a linear programming problem which is then formulated in the PYOMO optimization programming language. The building energy simulation software EnergyPlus is used to model the heating, ventilation, and air conditioning load of the battery energy storage system enclosure. Case studies are conducted for eight locations in the United States considering a nickel manganese cobalt oxide lithium ion battery type and whether the power conversion system is inside or outside the enclosure. The results show an increase of 42% to 300% in energy capacity size, 43% to 217% in power rating, and 43% to 296% increase in capital cost dependent on location. This analysis shows that the heating, ventilation, and air conditioning load can have a large impact on the optimal sizes and cost of a battery energy storage system and merit consideration in techno-economic studies.

25 ENERGY STORAGE↗

Pilgrim Hot Springs Building Dimensions and Energy Modeling

This dataset was created to model the anticipated heating load of a geothermal project in development for the historical site of Pilgrim Hot Springs, and adds to the history of geothermal studies at the site. Models include an historical building (Nun's Quarters), existing modern buildings (Caretaker's Cabin, Igloo, Visitor's Cabin, Staff Shower Hut), and planned building projects (Changing Room, Greenhouse). Modeling results were used to determine feasible geothermal system typologies. The previous study linked below ("Village of Solomon Development of Energy Efficiency Building Standards for New Construction") feeds in to this project. The dataset includes DWG drawings and AKwarm energy models (.hm2) of a subset of existing buildings at the site of Pilgrim Hot Springs. All buildings were modeled in their current state, and some were additionally modeled with improvements to the building envelope. Energy modeling results exported from AKwarm include .htm and .png images.

AKwarm↗

Energy based fracture initiation criterion for strain-crystallizing rubber-like materials with pre-existing cracks

Fracture prediction is indispensable for polymers, like rubbers, which have a broad range of applications mainly due to their high extensibility. The phenomenon known as strain-induced crystallization further contributes to the fracture toughness of certain rubbers. Here in this study, a criterion based on internal bond energy, incorporating the effects of crystallization, is proposed to predict fracture initiation in rubber-like materials with pre-existing cracks. First, a multi-scale mechanical model is developed for characterizing the behavior of rubber when subjected to both uniaxial and biaxial deformation states. At the microscale, both the amorphous and crystalline chain segments are modeled as elastic in order to consider the energy contribution by the molecular bond distortions. This internal energy is considered along with the entropic and crystalline free energy for each chain. In the chain model, the effects of loading condition and the relative orientation of a chain on its crystallinity are taken into account. At the macroscopic scale, an existing crystallinity distribution function is adapted and a mixed finite element formulation with an augmented Lagrangian multiplier is utilized to impose the incompressibility constraint. A non-affine maximal advance path constraint based homogenization model is utilized for bridging the two scales. Its potential to account for anisotropy in the stretched network compels the model to be preferable due to its physical significance, for the purpose of fracture modeling. The rigidity of the crystallites is accounted for by proposing a crystallite distortion energy in addition to the critical bond dissociation energy, for fracture initiation to occur. The model is validated by comparison with existing experimental results for both crystallizing and non-crystallizing rubbers. In addition to its potential to predict the material behavior when subjected to uniaxial and biaxial loading, the capability of the model to quantitatively estimate the effect of crystallization on fracture initiation is also verified.

36 MATERIALS SCIENCE↗

Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1 . The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformation processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.

36 MATERIALS SCIENCE↗

The mechanisms of ductile rupture

One of the most confounding controversies in the ductile fracture community is the large discrepancy between predicted and experimentally observed strain-to-failure values during shear-dominant loading. Currently presented solutions focus on better accounting for how the deviatoric stress state influences void growth or on measuring strain at the microscale rather than the macroscale. While these approaches are useful, they do not address a significant aspect of the problem: the only rupture micromechanisms that are generally considered are void nucleation, growth, and coalescence (for tensile-dominated loading), and shear-localization and void coalescence (for shear-dominated loading). Current phenomenological models have thus focused on predicting the competition between these mechanisms based on the stress state and the strain-hardening capacity of the material. However, in the present study, we demonstrate that there are at least five other failure mechanisms. Because these have long been ignored, little is known about how all seven mechanisms interact with one another or the factors that control their competition. These questions are addressed by characterizing the fracture process in three high-purity face-centered cubic (FCC) metals of medium-to-high stacking fault energy: copper, nickel, and aluminum. These data demonstrate that, for a given stress state and material, several mechanisms frequently work together in a sequential manner to cause fracture. The selection of a failure mechanism is significantly affected by the plasticity-induced microstructural evolution that occurs before tearing begins, which can create or eliminate sites for void nucleation. At the macroscale, failure mechanisms that do not involve cracking or pore growth were observed to facilitate subsequent void growth and coalescence processes. Even though the focus of this study is on damage accumulation in pure metals, these results are also applicable to understanding failure in engineering alloys.

36 MATERIALS SCIENCE↗

Controlled release of ibuprofen by meso–macroporous silica

Structured meso–macroporous silica was successfully synthesized from an O/W emulsion using decane as a dispersed phase. Sodium silicate solution, which acts as a silica source and a poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) (EO{sub 19}PO{sub 39}EO{sub 19}) denoted as P84 was used in order to stabilize the emulsion and as a mesopore template. The materials obtained were characterized through transmission electron microscopy (TEM), scanning electron microscopy (SEM), small-angle X-ray diffraction scattering (SAXS) and nitrogen adsorption–desorption isotherms. Ibuprofen (IBU) was selected as the model drug and loaded into ordered meso–macroporous materials. The effect of the materials’ properties on IBU drug loading and release was studied. The results showed that the loading of IBU increases as the macropore presence in the material is increased. The IBU adsorption process followed the Langmuir adsorption isotherm. A two-step release process, consisting of an initial fast release and then a slower release was observed. Macropores enhanced the adsorption capacity of the material; this was probably due to the fact that they allowed the drug to access internal pores. When only mesopores were present, ibuprofen was probably adsorbed on the mesopores close to the surface. Moreover, the more macropore present in the material, the slower the release behaviour observed, as the ibuprofen adsorbed in the internal pores had to diffuse along the macropore channels up to the surface of the material. The material obtained from a highly concentrated emulsion was functionalized with amino groups using two methods, the post-grafting mechanism and the co-condensation mechanism. Both routes improve IBU adsorption in the material and show good behaviour as a controlled drug delivery system. - Graphical abstract: Ibuprofen release profiles for the materials obtained from samples P84{sub m}eso (black diamonds), P84{sub 2}0% (white squares), P84{sub 5}0% (black triangles), P84{sub 7}5% (white diamonds), P84{sub 7}5% functionalized by grafting (black squares) and P84{sub 7}5% functionalized by co-condensation method (white triangles). Display Omitted - Highlights: • Ordered meso–macroporous material is used as a controlled delivery system for ibuprofen. • Incorporation of macropores in mesoporous silica improves ibuprofen adsorption. • Meso–macroporous structures provide a lower delivery than mesoporous silica. • APTES functionalization in meso–macroporous materials improves ibuprofen adsorption and delivery behaviour.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

N-induced soil acidification triggers metal stimulation of soil methane oxidation in a temperate steppe ecosystem

Methane (CH 4 ) is a potent greenhouse gas, and it is well established that low nitrogen (N) stimulates- and high N suppresses CH 4 oxidation in grassland ecosystems. Here, in this study, we examined the response of CH 4 uptake to long-term (>10 years) multi-level N additions in a temperate steppe of northern China. The N impacts on CH 4 uptake transitioned from positive to negative at the N addition rate of 4 g N m -2 y -1 . However, the high-N suppression on CH 4 uptake was partially relieved when the continuous (>10 years) high N inputs (16 g N m -2 y -1 to 64 g N m -2 y -1 ) caused soil pH drop to < 5.7. Further experiments revealed that continuous high-N inputs acidified soil to pH < 5.7 that released metal ions to stimulate monooxygenase enzyme activity; therefore, the CH 4 oxidation suppression was partially relieved under continuous N loading. Structural equation model results confirmed that metal ions, such as Iron (Fe 3+ ), Manganese (Mn 4+ ), and Copper (Cu) desorbed by soil particles, were negatively correlated with soil pH while positively correlated with CH 4 oxidation under high N inputs. These analyses suggested that continuous high N inputs-induced soil acidification can release previously bounded metal elements that partially alleviated the N suppression on CH 4 uptake. The N-induced soil acidification impacts on CH 4 uptake might play a critical role in global CH 4 cycling and deserve further investigation as external N inputs continue climbing.

59 BASIC BIOLOGICAL SCIENCES↗

Electrochemical Reactivity of Faceted β-Co(OH) 2 Single Crystal Platelet Particles in Alkaline Electrolytes

Oxygen evolution reaction is the kinetic bottleneck in the generation of H 2 gas through the electrolysis of water. Understanding how water is electrochemically converted to oxygen is key to the development of high-performance electrocatalysts that can enable energy storage technologies based on water to hydrogen fuel generation. The use of well-defined metal oxide systems allows for the isolation of spatial reactivity in bulk redox conversion and oxygen evolution reactions. Herein, we investigate the electrochemical reactivity of well-faceted single-crystalline β-Co(OH) 2 platelet particles in alkaline solutions as a function of pH, potential, and mass loading. A geometrical model that describes the electrochemically active surface area contributions for a porous electrode of stacked high-aspect ratio particles is developed, which pinpoints the origin of reactivity for redox conversion processes and oxygen evolution at the edge facets of the particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectrum of baryons with one charm quark

Diquark is employed to study the spectrum of baryons with one charm quark and two light quark within the mass loaded flux tube model. The spin-orbit interaction is taken into account based on the heavy quark symmetry. Some observed {Lambda}{sub c} and {Xi}{sub c} baryons are systematically classified with suggested J{sup P} quantum numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Force-free motion of a cold plasma during the current quench

Cold disruptive plasma tends to move during the current quench. Its motion is essentially force-free since the current quench timescale is resistive rather than Alfvénic. In contrast to the hot vertical displacement events, the frozen-in condition is violated in the cold plasma case, and the plasma motion is not governed by magnetic flux conservation but rather by its dissipation. In this paper, we present a numerical model of the cold plasma dynamics. This model predicts electromagnetic loads on the vacuum vessel, the plasma flow and density evolution, and the plasma centroid evolution. Our calculations include poloidal wall currents. Finally, we demonstrate their significant contribution to the force acting on the vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗