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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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A Systems Modeling Approach for Risk Management of Command File Errors
The main cause of commanding errors is often (but not always) due to procedures. Either lack of maturity in the processes, incompleteness of requirements or lack of compliance to these procedures. Other causes of commanding errors include lack of understanding of system states, inadequate communication, and making hasty changes in standard procedures in response to an unexpected event. In general, it's important to look at the big picture prior to making corrective actions. In the case of errors traced back to procedures, considering the reliability of the process as a metric during its' design may help to reduce risk. This metric is obtained by using data from Nuclear Industry regarding human reliability. A structured method for the collection of anomaly data will help the operator think systematically about the anomaly and facilitate risk management. Formal models can be used for risk based design and risk management. A generic set of models can be customized for a broad range of missions.
Reversible GaInP2 Surface Passivation by Water Adsorption: A Model System for Ambient-Dependent Photoluminescence
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System-of-Systems Approach for Integrated Energy Systems Modeling and Simulation
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The role of high-order electron correlation effects in a model system for non-valence correlation-bound anions
The diffusion Monte Carlo (DMC), auxiliary field quantum Monte Carlo (AFQMC), and equation-of-motion coupled cluster (EOM-CC) methods are used to calculate the electron binding energy (EBE) of the non-valence anion state of a model (H2O)4 cluster. Two geometries are considered, one at which the anion is unbound and the other at which it is bound in the Hartree–Fock (HF) approximation. It is demonstrated that DMC calculations can recover from the use of a HF trial wave function that has collapsed onto a discretized continuum solution, although larger EBEs are obtained when using a trial wave function for the anion that provides a more realistic description of the charge distribution and, hence, of the nodal surface. For the geometry at which the cluster has a non-valence correlation-bound anion, both the inclusion of triples in the EOM-CC method and the inclusion of supplemental diffuse d functions in the basis set are important. DMC calculations with suitable trial wave functions give EBE values in good agreement with our best estimate EOM-CC result. AFQMC using a trial wave function for the anion with a realistic electron density gives a value of the EBE nearly identical to the EOM-CC result when using the same basis set. For the geometry at which the anion is bound in the HF approximation, the inclusion of triple excitations in the EOM-CC calculations is much less important. The best estimate EOM-CC EBE value is in good agreement with the results of DMC calculations with appropriate trial wave functions.
Leaf optical system modeled as a stochastic process
A stochastic leaf radiation model based upon physical and physiological properties of dicot leaves has been developed. The model accurately predicts the absorbed, reflected, and transmitted radiation of normal incidence as a function of wavelength resulting from the leaf-irradiance interaction over the spectral interval of 0.40-2.50 micron. The leaf optical system has been represented as Markov process with a unique transition matrix at each 0.01-micron increment between 0.40 micron and 2.50 micron. Probabilities are calculated at every wavelength interval from leaf thickness, structure, pigment composition, and water content. Simulation results indicate that this approach gives accurate estimations of actual measured values for dicot leaf absorption, reflection, and transmission as a function of wavelength.
Building a generalized distributed system model
The key elements in the 1992-93 period of the project are the following: (1) extensive use of the simulator to implement and test - concurrency control algorithms, interactive user interface, and replica control algorithms; and (2) investigations into the applicability of data and process replication in real-time systems. In the 1993-94 period of the project, we intend to accomplish the following: (1) concentrate on efforts to investigate the effects of data and process replication on hard and soft real-time systems - especially we will concentrate on the impact of semantic-based consistency control schemes on a distributed real-time system in terms of improved reliability, improved availability, better resource utilization, and reduced missed task deadlines; and (2) use the prototype to verify the theoretically predicted performance of locking protocols, etc.
Multiyear Plan for Validation of EnergyPlus Multi-Zone HVAC System Modeling using ORNL's Flexible Research Platform
This document describes the Oak Ridge National Laboratory (ORNL) multiyear experimental plan for validation and uncertainty characterization of whole-building energy simulation for a multi-zone research facility using a traditional rooftop unit (RTU) as a baseline heating, ventilating, and air conditioning (HVAC) system. The project’s overarching objective is to increase the accuracy of energy simulation tools by enabling empirical validation of key inputs and algorithms. Doing so is required to inform the design of increasingly integrated building systems and to enable accountability for performance gaps between design and operation of a building. The project will produce documented data sets that can be used to validate key functionality in different energy simulation tools and to identify errors and inadequate assumptions in simulation engines so that developers can correct them. ASHRAE Standard 140, Method of Test for the Evaluation of Building Energy Analysis Computer Programs (ASHRAE 2004), currently consists primarily of tests to compare different simulation programs with one another. This project will generate sets of measured data to enable empirical validation, incorporate these test data sets in an extended version of Standard 140, and apply these tests to the Department of Energy’s (DOE) EnergyPlus software (EnergyPlus 2016) to initiate the correction of any significant deficiencies. The fitness-for-purpose of the key algorithms in EnergyPlus will be established and demonstrated, and vendors of other simulation programs will be able to demonstrate the validity of their products. The data set will be equally applicable to validation of other simulation engines as well.
A Conceptual Aerospace Vehicle Structural System Modeling, Analysis and Design Process
A process for aerospace structural concept analysis and design is presented, with examples of a blended-wing-body fuselage, a multi-bubble fuselage concept, a notional crew exploration vehicle, and a high altitude long endurance aircraft. Aerospace vehicle structures must withstand all anticipated mission loads, yet must be designed to have optimal structural weight with the required safety margins. For a viable systems study of advanced concepts, these conflicting requirements must be imposed and analyzed early in the conceptual design cycle, preferably with a high degree of fidelity. In this design process, integrated multidisciplinary analysis tools are used in a collaborative engineering environment. First, parametric solid and surface models including the internal structural layout are developed for detailed finite element analyses. Multiple design scenarios are generated for analyzing several structural configurations and material alternatives. The structural stress, deflection, strain, and margins of safety distributions are visualized and the design is improved. Over several design cycles, the refined vehicle parts and assembly models are generated. The accumulated design data is used for the structural mass comparison and concept ranking. The present application focus on the blended-wing-body vehicle structure and advanced composite material are also discussed.
Optimization of Refrigerant Compositions for Low-GWP Refrigerant Mixtures Using Segment-by-segment Heat Exchanger and Detailed System Models
The recently introduced hydrofluoroolefin (HFO) refrigerants, including R1234yf and R1234ze(E), have significantly lower global warming potentials (GWPs) than traditional hydrofluorocarbon (HFC) refrigerants like R410A. However, prior tests show that direct drop-in of pure R1234yf or R1234ze(E) into equipment designed for R410A results in a decrease in heat exchanger capacity and the system coefficient of performance. The primary reason is the lower in-tube heat transfer performance of R1234yf and R1234ze(E) compared with that of R410A. To address this issue, previous studies have mixed the mildly flammable HFC R32 with HFOs to improve system performance, with HFC R125 also added to suppress flammability. Previous studies selected compositions based on simple cycle analyses and did not consider modifications of the heat exchanger circuitry configuration to adapt to the new refrigerants. This study presents a novel multi-objective optimization approach to design a refrigerant composition that maximizes energy efficiency within flammability and GWP limits. The approach in this work simultaneously optimizes mixture composition and heat exchanger circuitry configuration. A case study on a rooftop unit indicates that, compared with mixture-only optimization, simultaneous optimization of mixture and heat exchanger circuitry yields a 5.9% improvement in cycle efficiency and a 48.6% reduction in refrigerant flammability with a GWP of 268. Circuitry optimization using refrigerants with different temperature glides shows that the larger the temperature glide is, the larger EER improvement is obtained. The results show that zeotropic blends with a large temperature glide are more sensitive to the refrigerant circuitry than pure refrigerants and may suffer significant performance degradation with subpar heat exchanger circuitry design. The proposed optimization approach is generally applicable to mixtures with any number of components. Using this approach to design a HVAC system can yield higher system efficiency within flammability and GWP constraints.
Basin and Petroleum System Modeling of Gas Hydrate Deposits in the Walker Ridge Area, Northern Gulf of Mexico - Poster
Poster presented by NETL at ICGH, 06/17 - Abstract:<p><br></p><p>We are currently constructing an Earth model of the Terrebonne Basin for comprehensive 3D modeling. Well data and a high-quality 3D seismic survey underpin the geologic conditions for the model. Additional model constraints include basal heat flow, seafloor temperature, and paleowater depth through time. Our initial investigation comprises the development of a “pseudo” 2D model centered on the deep WR313 #001 well. We are using this test case to establish the workflow for integrating BPSM with gas hydrate analyses; this will eventually be applied to the entire mini-basin. </p><p><br></p><p>A key aspect of investigating the gas hydrate system with BPSM is integrating it with the other active petroleum system(s) in the region, because the methane in hydrate deposits can derive from both biogenic and thermogenic sources. Some of the questions we may consider are: What is the history of these deposits with respect to the gas hydrate stability zone, recognizing that this area is not one characterized by simple continuous sedimentation and subsidence, but instead by periodic uplift, tilting, plate rotation, sea-level change, salt tectonics, and evolution of temperature gradients. </p><p><br></p><p>In conclusion, BPSM has been called the ‘great integrator’ in petroleum exploration. Development of a BPSM model of gas hydrates in the Terrebonne Basin of the northern GoM will provide a vehicle within which to integrate other early exploration and assessment research being conducted on gas hydrates, such as in frontier areas like Japan, as a potential resource likely to provide many decades of energy if proven to be commercially producible</p>
Control System Modeling for the Thirty Meter Telescope Primary Mirror
The Thirty Meter Telescope primary mirror is composed of 492 segments that are controlled to high precision in the presence of wind and vibration disturbances, despite the interaction with structural dynamics. The higher bandwidth and larger number of segments compared with the Keck telescopes requires greater attention to modeling to ensure success. We focus here on the development and validation of a suite of quasi-static and dynamic modeling tools required to support the design process, including robustness verification, performance estimation, and requirements flowdown. Models are used to predict the dynamic response due to wind and vibration disturbances, estimate achievable bandwidth in the presence of control-structure-interaction (CSI) and uncertainty in the interaction matrix, and simulate and analyze control algorithms and strategies, e.g. for control of focus-mode, and sensor calibration. Representative results illustrate TMT performance scaling with parameters, but the emphasis is on the modeling framework itself.
Integrated Transportation-Energy Systems Modeling
Transportation is currently the least-diversified energy demand sector, with over 90% of global transportation energy use coming from petroleum product. After over a century of petroleum dominance, however, many leading experts anticipate major electrification trends that could disrupt the transportation energy demand landscape. These changes in electricity demand complement profound changes happening within electric power supply systems, including integration of variable renewables, distributed generation and storage, and greater participation in power system planning and operations from traditionally passive consumers. This broader context underscores the importance of understanding how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system and the opportunity to leverage flexible EV charging to more cost-effectively balance demand and supply. This talk provides an overview of recent findings on infrastructure requirements to support EV adoption, integration challenges and the impact of EV on power systems, and opportunities to leverage flexible (or smart) EV charging to support power system planning and operations.
Understanding the Solid-State Electrode–Electrolyte Interface of a Model System Using First-Principles Statistical Mechanics and Thin-Film X-ray Characterization
Intermixing of atomic species at the electrode-electrolyte boundaries can impact the properties of the interfaces in solid-state batteries. Herein, this work uses first-principles statistical mechanics along with experimental characterization to understand intermixing at the electrode-electrolyte interface. For the model presented in this work, lithium manganese oxide (LiMn 2 O 4 , LMO) and lithium lanthanum titanate (Li 3x La 2/3-x TiO 3 , LLTO) are employed as the cathode and electrolyte, respectively. The results of the computational work show that Ti-Mn intermixing at the interface is significant at synthesis temperatures. The experimental results in this work find that, at some critical temperatures between 600 and 700 degrees C for material preparation, the interface of LLTO-LMO becomes blurred. Calculations predict that the interface is unstable with regard to Ti-Mn intermixing starting at 0 K, suggesting that the critical temperature found in the experiment is related to kinetics. The work overall suggests that, in designing a solid-state battery, the fundamental reactions such as intermixing need to be considered.
Biological neural networks as model systems for designing future parallel processing computers
One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.
The development of spaceflight experiments with Arabidopsis as a model system in gravitropism studies
Experiments with Arabidopsis have been developed for spaceflight studies in the European Space Agency's Biorack module. The Biorack is a multiuser facility that is flown on the United States Space Shuttle and serves as a small laboratory for studying cell and developmental biology in unicells, plants, and small invertebrates. The purpose of our spaceflight research was to investigate the starch-statolith model for gravity perception by studying wild-type (WT) and three starch-deficient mutants of Arabidopsis. Since spaceflight opportunities for biological experimentation are scarce, the extensive ground-based testing described in this paper is needed to ensure the success of a flight project. Therefore, the specific aims of our ground-based research were: (1) to modify the internal configuration of the flight hardware, which originally was designed for large lentil seeds, to accommodate small Arabidopsis seeds; (2) to maximize seed germination in the hardware; and (3) to develop favorable conditions in flight hardware for the growth and gravitropism of seedlings. The hardware has been modified, and growth conditions for Arabidopsis have been optimized. These experiments were successfully flown on two Space Shuttle missions in 1997.
A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events
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Development and testing of laser Doppler system components for wake vortex monitoring. Volume 1: Scanner development, laboratory and field testing and system modeling
A servo-controlled range/elevation scanner for the laser Doppler velocimeter (LDV) was developed and tested in the field to assess its performance in detecting and monitoring aircraft trailing vortices in an airport environment. The elevation scanner provides a capability to manually point the LDV telescope at operator chosen angles from 3.2 deg. to 89.6 deg within 0.2 deg, or to automatically scan the units between operator chosen limits at operator chosen rates of 0.1 Hz to 0.5 Hz. The range scanner provides a capability to manually adjust the focal point of the system from a range of 32 meters to a range of 896 meters under operator control, or to scan between operator chosen limits and at rates from 0.1 Hz to 6.9 Hz. The scanner controls are designed to allow simulataneous range and elevation scanning so as to provide finger scan patterns, arc scan patterns, and vertical line scan patterns. The development and testing of the unit is discussed, along with a fluid dynamic model of the wake vortex developed in a laser Doppler vortex sensor simulation program.