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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

NREL RSF Weather Data 2011

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Weather data form the RSF systems energy model. The weather data was used to contextualize and compare energy use data like heating and cooling. The weather data was also used by the RSF Energy Model to model the energy use of the RSF. Energy Model data and Measured Energy data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.

2011↗
DOE OSTI2011

IMPACTS OF SMALL COLUMN ION EXCHANGE STREAMS ON DWPF GLASS FORMULATION: KT08, KT09, AND KT10-SERIES GLASS COMPOSITIONS

This report is the fourth in a series of studies of the impacts of the addition of Crystalline Silicotitanate (CST) and Monosodium Titanate (MST) from the Small Column Ion Exchange (SCIX) process on the Defense Waste Processing Facility (DWPF) glass waste form and the applicability of the DWPF process control models. MST from the Salt Waste Processing Facility (SWPF) is also considered in the study. The KT08-series of glasses was designed to evaluate any impacts of the inclusion of uranium and thorium in glasses containing the SCIX components. The KT09-series of glasses was designed to study the effect of increasing Al{sub 2}O{sub 3} and K{sub 2}O concentrations on the propensity for crystallization of titanium containing phases in high TiO{sub 2} concentration glasses. Earlier work on the KT05-series glasses recommended that the impact of these two components be studied further. Increased Al{sub 2}O{sub 3} concentrations have been shown to improve the properties and performance of high waste loading glasses, and K{sub 2}O has been reported to improve the retention of TiO{sub 2} in silicate glasses. The KT10-series of compositions was designed to evaluate any impacts of the SCIX components at concentrations 50% higher than currently projected.a The glasses were fabricated in the laboratory and characterized to identify crystallization, to verify chemical compositions, to measure viscosity, and to measure durability. Liquidus temperature measurements for the KT10-series glasses are underway and will be reported separately. All but one of the KT08-series glasses were found to be amorphous by X-ray diffraction (XRD). One of the slowly cooled glasses contained a small amount of trevorite, which had no practical impact on the durability of the glass and is typically found in DWPF-type glasses. The measured Product Consistency Test (PCT) responses for the KT08-series glasses are well predicted by the DWPF models. The viscosities of the KT08-series glasses were generally well predicted by the DWPF model. No unexpected issues were encountered when uranium and thorium were added to the glasses with SCIX components. Increased Al{sub 2}O{sub 3} concentrations were not successful in preventing the formation of iron titanate crystals in the KT09-series glasses. Increased K{sub 2}O concentrations were successful in hindering the formation of iron titanates in some of the glasses after the canister centerline cooled (CCC) heat treatment. However, this result did not apply to all of the CCC versions of the glasses, indicating a compositional dependence of this effect. In addition, high concentrations of K{sub 2}O have been shown to hinder the ability of the DWPF durability and viscosity models to predict the performance of these glasses. The usefulness of increased K{sub 2}O concentrations in preventing the formation of iron titanates may therefore be limited. Further characterization was not performed for the KT09-series glasses since the type of crystallization formed was the characteristic of interest for these compositions. All of the KT10-series glasses were XRD amorphous, regardless of heat treatment. Chemical composition measurements showed that the glasses met the targeted concentrations for each oxide. In general, the measured PCT responses of the KT10-series glasses were well predicted by the DWPF models. The measured, normalized release values for silicon for some of the glasses fell above the 95% confidence interval for the predicted values; however, the PCT responses for these glasses remain considerably lower than that of the benchmark Environmental Assessment (EA) glass. The viscosities of the KT10-series glasses were generally well predicted by the DWPF model. The next step in this study will be to compile all of the data developed and further compare the measured properties and performance with those predicted by the current DWPF Product Composition Control System (PCCS) models. Recommendations will then be made as to which models, if any, may need to be modified in order to accommodate the material from SCIX into DWPF glass production.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

A test of the hierarchical model of litter decomposition

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle–climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the con- trolling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France—and capturing both within and among site variation in putative controls—we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

SU-E-J-273: Simulation of the Radiation Response of Hypoxic Tumors

Purpose: In radiotherapy, it is important to predict the response of tumour to irradiation prior to the treatment. Mathematical modelling of tumour control probability (TCP) based on the dose distribution, medical imaging and other biological information may help to improve this prediction and to optimize the treatment plan. The aim of this work is to develop an image based 3D multiscale radiobiological model, which describes the growth and the response to radiotherapy of hypoxic tumors. Methods: The computer model is based on voxels, containing tumour, normal (including capillary) and dead cells. Killing of tumour cells due to irradiation is calculated by the Linear Quadratic Model (extended for hypoxia), and the proliferation and resorption of cells are modelled by exponential laws. The initial shape of the tumours is taken from CT images and the initial vascular and cell density information from PET and/or MR images. Including the fractionation regime and the physical dose distribution of the radiation treatment, the model simulates the spatial-temporal evolution of the tumor. Additionally, the dose distribution may be biologically optimized. Results: The model describes the appearance of hypoxia during tumour growth and the reoxygenation processes during radiotherapy. Among other parameters, the TCP is calculated for different dose distributions. The results are in accordance with published results. Conclusion: The simulation model may contribute to the understanding of the influence of biological parameters on tumor response during treatment, and specifically on TCP. It may be used to implement dose-painting approaches. Experimental and clinical validation is needed. This study is supported by a grant from the Ministry of Education of Chile, Programa Mece Educacion Superior (2)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Design and analysis of a wake model for spatially heterogeneous flow

Abstract. Methods of turbine wake modeling are being developed to more accurately account for spatially variant atmospheric conditions within wind farms. Most current wake modeling utilities are designed to apply a uniform flow field to the entire domain of a wind farm. When this method is used, the accuracy of power prediction and wind farm controls can be compromised depending on the flow-field characteristics of a particular area. In an effort to improve strategies of wind farm wake modeling and power prediction, FLOw Redirection and Induction in Steady State (FLORIS) was developed to implement sophisticated methods of atmospheric characterization and power output calculation. In this paper, we describe an adapted FLORIS model that features spatial heterogeneity in flow-field characterization. This model approximates an observed flow field by interpolating from a set of atmospheric measurements that represent local weather conditions. The objective of this method is to capture heterogeneous atmospheric effects caused by site-specific terrain features, without explicitly modeling the geometry of the wind farm terrain. The implemented adaptations were validated by comparing the simulated power predictions generated from FLORIS to the actual recorded wind farm output from the supervisory control and data acquisition (SCADA) recordings and large eddy simulations (LESs). When comparing the performance of the proposed heterogeneous model to homogeneous FLORIS simulations, the results show a 14.6 % decrease for mean absolute error (MAE) in wind farm power output predictions for cases using wind farm SCADA data and a 18.9 % decrease in LES case studies. The results of these studies also indicate that the efficacy of the proposed modeling techniques may vary with differing site-specific operational conditions. This work quantifies the accuracy of wind plant power predictions under heterogeneous flow conditions and establishes best practices for atmospheric surveying for wake modeling.

17 WIND ENERGY↗
DOE OSTI2014

NREL RSF Measured Data 2011

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Measured Energy Data from the RSF Systems Model. The data includes a csv with measured data from NREL's Research and Support Facility (RSF) for 2011. The dataset contains hourly data for: Total Cooling (kW)- Total Heating (kW)- Total Mechanical (kW)- Total Lighting (kW)- Total Plug Loads (kW)- Total Data Center (kW)- Total Building (kW)- PV (kW)- Building Net (kW). Energy Model data and Weather data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.

2011↗
DOE OSTI2019

Controlling the extent of atomic ordering in intermetallic alloys through additive manufacturing

Control of the atomic structure, as measured by the extent of the embrittling B2 chemically ordered phase, is demonstrated in intermetallic alloys through additive manufacturing (AM) and characterized using high fidelity neutron diffraction. As a layer-by-layer rapid solidification process, AM was employed to suppress the extent of chemically ordered B2 phases in a soft ferromagnetic Fe-Co alloy, as a model material system of interest to electromagnetic applications. The extent of atomic ordering was found to be insensitive to the spatial location within specimens and insinuates that the thermal conditions within only a few AM layers were most influential in controlling the microstructure, in agreement with the predictions from a thermal model for welding. Analysis of process parameter effects on ordering found that suppression of B2 phase was the result of an increased average cooling rate during processing. AM processing parameters, namely interlayer interval time and build velocity, were used to systematically control the relative fraction of ordered B2 phase in specimens from 0.49 to 0.72. Hardness of AM specimens was more than 150% higher than conventionally processed bulk material. Implications for tailoring microstructures of intermetallic alloys are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Prediction of The TREAT Facility Power and Temperature of Sirius-2c Nuclear Propulsion Fuel Experiment

This paper presents simulation results of the Sirius-2c full power experiment that was performed at the TREAT facility to support experiment modeling and transient analysis of the NASA-sponsored Sirius series of experiments for nuclear thermal propulsion applications. We presents a novel approach to predict the control rod motion and power of the reactor and the temperature of the specimen during transient experiments using the Griffin and Bison packages of the Multiphysics Object Oriented Simulation Environment (MOOSE). First, the model predicts the transient rod motion that results in the desired reactor power shape. Then, the temperature of the specimen is predicted based on the power deposited in the specimen. The prediction results are in good agreement with the measured reactor power and control rod position and over-predicted the specimen temperature which is mainly related to specimen surface emissivities. The reactor reaches a peak power of 80 MW and a specimen temperature of 2500 K and considering the right specimen emissivities the predicted temperature is in an excellent agreement with the measured values. This model can be utilized in helping and supporting the design and optimization a new experiments that are going to be irradiated in the TREAT facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control: Maximization of wind plant AEP by optimization of layout and wake control

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.

17 WIND ENERGY↗
DOE OSTI2021

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Physical Models of Cognition

This paper presents and discusses physical models for simulating some aspects of neural intelligence, and, in particular, the process of cognition. The main departure from the classical approach here is in utilization of a terminal version of classical dynamics introduced by the author earlier. Based upon violations of the Lipschitz condition at equilibrium points, terminal dynamics attains two new fundamental properties: it is spontaneous and nondeterministic. Special attention is focused on terminal neurodynamics as a particular architecture of terminal dynamics which is suitable for modeling of information flows. Terminal neurodynamics possesses a well-organized probabilistic structure which can be analytically predicted, prescribed, and controlled, and therefore which presents a powerful tool for modeling real-life uncertainties. Two basic phenomena associated with random behavior of neurodynamic solutions are exploited. The first one is a stochastic attractor ; a stable stationary stochastic process to which random solutions of a closed system converge. As a model of the cognition process, a stochastic attractor can be viewed as a universal tool for generalization and formation of classes of patterns. The concept of stochastic attractor is applied to model a collective brain paradigm explaining coordination between simple units of intelligence which perform a collective task without direct exchange of information. The second fundamental phenomenon discussed is terminal chaos which occurs in open systems. Applications of terminal chaos to information fusion as well as to explanation and modeling of coordination among neurons in biological systems are discussed. It should be emphasized that all the models of terminal neurodynamics are implementable in analog devices, which means that all the cognition processes discussed in the paper are reducible to the laws of Newtonian mechanics.

Zak, Michail↗
NASA NTRS1992

Intelligent sensor-model automated control of PMR-15 autoclave processing

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Hart, S.↗
DOE OSTI2010

Abiotic transformation of high explosives by freshly precipitated iron minerals in aqueous Fe¹¹ solutions

Zerovalent iron barriers have become a viable treatment for field-scale cleanup of various ground water contaminants. While contact with the iron surface is important for contaminant destruction, the interstitial pore water within and near the iron barrier will be laden with aqueous, adsorbed and precipitated FeII phases. These freshly precipitated iron minerals could play an important role in transforming high explosives (HE). Our objective was to determine the transformation of RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine), HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine), and TNT (2,4,6-trinitrotoluene) by freshly precipitated iron FeII/FeIII minerals. This was accomplished by quantifying the effects of initial FeII concentration, pH, and the presence of aquifer solids (FeIII phases) on HE transformation rates. Results showed that at pH 8.2, freshly precipitated iron minerals transformed RDX, HMX, and TNT with reaction rates increasing with increasing FeII concentrations. RDX and HMX transformations in these solutions also increased with increasing pH (5.8-8.55). By contrast, TNT transformation was not influenced by pH (6.85-8.55) except at pH values <6.35. Transformations observed via LC/MS included a variety of nitroso products (RDX, HMX) and amino degradation products (TNT). XRD analysis identified green rust and magnetite as the dominant iron solid phases that precipitated from the aqueous FeII during HE treatment under anaerobic conditions. Geochemical modeling also predicted FeII activity would likely be controlled by green rust and magnetite. These results illustrate the important role freshly precipitated FeII/FeIII minerals in aqueous FeII solutions play in the transformation of high explosives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Theoretical Investigation of H₂ Oxidation on the Sr 2 Fe 1.5 Mo 0.5 O 6 (001) Perovskite Surface Under Anodic Solid Oxide Fuel Cell Conditions

Periodic density functional theory (DFT) calculations and microkinetic modeling are used to investigate the electrochemical oxidation of H₂ fuel on the (001) surface of Sr 2 Fe 1.5 Mo 0.5 O 6 (SFMO) perovskite under anodic solid oxide fuel cell conditions. Three surface models with different Fe/Mo ratios in the topmost layer-identified by ab initio thermodynamic analysis-are used to investigate the H₂ oxidation mechanism. A microkinetic analysis that considers the effects of anode bias potential suggests that a higher Mo concentration in the surface increases the activity of the surface toward H₂ oxidation. At operating voltage and anodic SOFC conditions, the model predicts that water desorption is rate-controlling and that stabilizing the oxygen vacancy structure increases the overall rate for H₂ oxidation. Although we find that Mo plays a crucial role in improving catalytic activity of SFMO, under fuel cell operating conditions, the Mo content in the surface layer tends to be very low. On the basis of these results and in agreement with previous experimental observations, a strategy for improving the overall electrochemical performance of SFMO is increasing the Mo content or adding small amounts of an active transition metal, such as Ni, to the surface to lower the oxygen vacancy formation energy of the SFMO surface.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model

Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large‐eddy simulation (LES). Our approach involves representing the cloud size distribution and the total cloud area using a revised Lotka‐Volterra model and ridge linear model, respectively. The physical interpretation of the total cloud area and coefficients obtained from the optimization of the models reveals three stages probably interpreted by dominant processes: the formation of new clouds, the growth of single clouds, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale‐aware parameterizations of shallow‐convective clouds in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

CO 2 absorption from simulated flue gas in a bubble column

Carbon dioxide (CO 2 ) absorption from power plant generated flue gas is studied for CO 2 emissions reduction. Amino acid alkaline solvents have the potential to reduce the energy required for solvent regeneration. Here, we focus on CO 2 absorption by amino acid alkaline solvents in a bubble column. Important parameters characterizing the reactor, e.g., bubble size, liquid-phase dispersion coefficient, and gas holdup, are experimentally determined. A theoretical model based upon transient mass and energy balances for the chemical species involved is presented. Simulation results are compared to experimental data. The model can be used to predict, optimize, and control CO 2 absorption in industrial-scale applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Modeling and control of plasma rotation for NSTX using neoclassical toroidal viscosity and neutral beam injection

A model-based feedback system is presented to control plasma rotation in a magnetically confined toroidal fusion device, to maintain plasma stability for long-pulse operation. This research uses experimental measurements from the National Spherical Torus Experiment (NSTX) and is aimed at controlling plasma rotation using two different types of actuation: momentum from injected neutral beams and neoclassical toroidal viscosity generated by three-dimensional applied magnetic fields. Based on the data-driven model obtained, a feedback controller is designed, and predictive simulations using the TRANSP plasma transport code show that the controller is able to attain desired plasma rotation profiles given practical constraints on the actuators and the available measurements of rotation.

feedback control↗
DOE OSTI2017

Full-Scale Field Test of Wake Steering

Wind farm control, in which turbine controllers are coordinated to improve farmwide performance, is an active field of research. One form of wind farm control is wake steering, in which a turbine is yawed to the inflow to redirect its wake away from downstream turbines. Wake steering has been studied in depth in simulations as well as in wind tunnels and scaled test facilities. This work performs a field test of wake steering on a full-scale turbine. In the campaign, the yaw controller of the turbine has been set to track different yaw misalignment set points while a nacelle-mounted lidar scans the wake at several ranges downwind. The lidar measurements are combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast. In conclusion, these measurements are then compared to the predictions of a wind farm control-oriented model of wakes.

17 WIND ENERGY↗