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NASA NTRS2000

Optimization of Car Body under Constraints of Noise, Vibration, and Harshness (NVH), and Crash

To be competitive on the today's market, cars have to be as light as possible while meeting the Noise, Vibration, and Harshness (NVH) requirements and conforming to Government-man dated crash survival regulations. The latter are difficult to meet because they involve very compute-intensive, nonlinear analysis, e.g., the code RADIOSS capable of simulation of the dynamics, and the geometrical and material nonlinearities of a thin-walled car structure in crash, would require over 12 days of elapsed time for a single design of a 390K elastic degrees of freedom model, if executed on a single processor of the state-of-the-art SGI Origin2000 computer. Of course, in optimization that crash analysis would have to be invoked many times. Needless to say, that has rendered such optimization intractable until now. The car finite element model is shown. The advent of computers that comprise large numbers of concurrently operating processors has created a new environment wherein the above optimization, and other engineering problems heretofore regarded as intractable may be solved. The procedure, shown, is a piecewise approximation based method and involves using a sensitivity based Taylor series approximation model for NVH and a polynomial response surface model for Crash. In that method the NVH constraints are evaluated using a finite element code (MSC/NASTRAN) that yields the constraint values and their derivatives with respect to design variables. The crash constraints are evaluated using the explicit code RADIOSS on the Origin 2000 operating on 256 processors simultaneously to generate data for a polynomial response surface in the design variable domain. The NVH constraints and their derivatives combined with the response surface for the crash constraints form an approximation to the system analysis (surrogate analysis) that enables a cycle of multidisciplinary optimization within move limits. In the inner loop, the NVH sensitivities are recomputed to update the NVH approximation model while keeping the Crash response surface constant. In every outer loop, the Crash response surface approximation is updated, including a gradual increase in the order of the response surface and the response surface extension in the direction of the search. In this optimization task, the NVH discipline has 30 design variables while the crash discipline has 20 design variables. A subset of these design variables (10) are common to both the NVH and crash disciplines. In order to construct a linear response surface for the Crash discipline constraints, a minimum of 21 design points would have to be analyzed using the RADIOSS code. On a single processor in Origin 2000 that amount of computing would require over 9 months! In this work, these runs were carried out concurrently on the Origin 2000 using multiple processors, ranging from 8 to 16, for each crash (RADIOSS) analysis. Another figure shows the wall time required for a single RADIOSS analysis using varying number of processors, as well as provides a comparison of 2 different common data placement procedures within the allotted memories for each analysis. The initial design is an infeasible design with NVH discipline Static Torsion constraint violations of over 10%. The final optimized design is a feasible design with a weight reduction of 15 kg compared to the initial design. This work demonstrates how advanced methodology for optimization combined with the technology of concurrent processing enables applications that until now were out of reach because of very long time-to-solution.

Kodiyalam, Srinivas↗

DOE OSTI2020

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 1

Due to continuing global energy market trends, driven heavily by the abundant preserves of natural gas, there is an immediate need to reduce costs associated with operation and maintenance (O&M) for the current domestic nuclear power industry and for future reactor developments. This is to ensure that nuclear power generation remains an economically competitive and viable option in the energy market. O&M costs include labor-intensive preventive maintenance (PM) programs, which involve manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets, irrespective of their condition. This has resulted in an expensive, labor-centric business model to achieve high capacity factors. Fortunately, there are technologies (advanced sensors, data analytics, and risk assessment methodologies) that can enable the transition from a labor-centric business model to a technology-centric business model. The technology-centric business model will result in a significant reduction of PM activities, laying the foundation for real-time condition assessment of plant assets, reducing overall labor and part costs. To enable this transition, PKMJ Technical Services LLC is partnering with the U.S. Department of Energy’s Idaho National Laboratory (operated by the Battelle Energy Alliance, LLC) and the Public Services Enterprise Group (PSEG) Nuclear, LLC in the Integrated Risk-Informed Condition-Based Maintenance Capability and Automated Platform Project. In this report, the configuration of a digital cloud platform using Microsoft Azure is discussed, data from the PSEG Salem Nuclear Generating Station Units 1 & 2 are imported into a digital cloud platform, and the data is used for an evaluation of several key areas: cost impact analysis, risk-informed model development, and preventive maintenance strategy optimization. First, the cost impact analysis reviews which plant assets are potential good candidates for condition-based monitoring. Next, INL utilized the data in their local environment to develop the risk-informed model; which provides estimates of failure rates and probability of failures of assets based upon their past performance. The developed model is performed on assets selected from the cost impact analysis. Lastly, engineers assess the preventive maintenance strategy for the selected assets at PSEG against maintenance strategies in the nuclear industry for similar assets to potentially identify acceptable justification for the extension of current maintenance frequencies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1994

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Iverson, David L.↗

DOE OSTI2024

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗

DOE OSTI2019

Engineering uranyl-chelating peptides from NikR for electrochemical peptide-based sensing applications

We have, for the first time, designed three uranyl-chelating peptides by modeling after the uranyl binding pocket found in a mutated Ni(II)-dependent transcriptional repressor (NikR). All three thiolated and methylene blue (MB)-modified peptides, NikR-5, NikR-11, and NikR-15, contain the five core amino acids responsible for target recognition, but the two longer peptides have either one or two additional glycine residues in between the five amino acids. These three peptide probes were then used in the fabrication of electrochemical peptide-based (E-PB) uranyl ion (U(VI)) sensors, with the goal of elucidating the effects of the added glycine residues and probe flexibility on target recognition. The sensing mechanism is similar to other “signal-off” E-PB sensors, in which binding of the target rigidifies the probe, resulting in a decrease in the redox signal from the tethered MB label. Although all three sensors responded to U(VI), the NikR-15 sensor's behavior was irreproducible and thus precluded from the rest of the study. The NikR-11 sensor showed the largest response to U(VI), whereas the NikR-5 sensor showed higher specificity for U(VI). The limit of detection was 50 nM for both sensors, which is well below the U.S. Environmental Protection Agency maximum contaminant level for uranium. Both sensors were further tested and proven functional in a 50% synthetic aquifer sample. Overall, the NikR-11 sensor, fabricated with the 11-amino acid probe, is deemed the optimal design. Incorporating glycine residues is a strategic way to lengthen the peptide slightly to improve target binding. This simple yet versatile approach to recreating binding pockets on electrode surfaces can potentially be employed in the design of other E-PB and surface-based metal ion sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yield sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.

09 BIOMASS FUELS↗

DOE OSTI2016

Workshop Report: Systems Biology for Organotypic Cell Cultures

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

3D models↗

NASA NTRS2018

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

Pisani, William A.↗

DOE OSTI2012

Structural basis for immunization with postfusion respiratory syncytial virus fusion F glycoprotein (RSV F) to elicit high neutralizing antibody titers

Respiratory syncytial virus (RSV), the main cause of infant bronchiolitis, remains a major unmet vaccine need despite more than 40 years of vaccine research. Vaccine candidates based on a chief RSV neutralization antigen, the fusion (F) glycoprotein, have foundered due to problems with stability, purity, reproducibility, and potency. Crystal structures of related parainfluenza F glycoproteins have revealed a large conformational change between the prefusion and postfusion states, suggesting that postfusion F antigens might not efficiently elicit neutralizing antibodies. We have generated a homogeneous, stable, and reproducible postfusion RSV F immunogen that elicits high titers of neutralizing antibodies in immunized animals. The 3.2-{angstrom} X-ray crystal structure of this substantially complete RSV F reveals important differences from homology-based structural models. Specifically, the RSV F crystal structure demonstrates the exposure of key neutralizing antibody binding sites on the surface of the postfusion RSV F trimer. This unanticipated structural feature explains the engineered RSV F antigen's efficiency as an immunogen. This work illustrates how structural-based antigen design can guide the rational optimization of candidate vaccine antigens.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1973

Engineering models of the Venus atmosphere.

Engineering models of the Venus atmosphere are presented for use in spacecraft design and mission planning. The models are developed from (1) data measured by the U.S. Mariner 5 and USSR Venera spacecraft, (2) earth-based measurements, and (3) theory which best satisfies the observations. The models include a most probable model and models for extremes of molecular mass and solar activity. In addition to the basic engineering models, other atmospheric characteristics and parameters affecting the models are discussed including planetary radius, atmospheric composition and clouds.

Noll, R. B.↗

NASA NTRS1993

Rotary engine performance computer program (RCEMAP and RCEMAPPC): User's guide

This report is a user's guide for a computer code that simulates the performance of several rotary combustion engine configurations. It is intended to assist prospective users in getting started with RCEMAP and/or RCEMAPPC. RCEMAP (Rotary Combustion Engine performance MAP generating code) is the mainframe version, while RCEMAPPC is a simplified subset designed for the personal computer, or PC, environment. Both versions are based on an open, zero-dimensional combustion system model for the prediction of instantaneous pressures, temperature, chemical composition and other in-chamber thermodynamic properties. Both versions predict overall engine performance and thermal characteristics, including bmep, bsfc, exhaust gas temperature, average material temperatures, and turbocharger operating conditions. Required inputs include engine geometry, materials, constants for use in the combustion heat release model, and turbomachinery maps. Illustrative examples and sample input files for both versions are included.

Bartrand, Timothy A.↗

DOE OSTI2018

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

The state-of-the-art multiscale modeling of GPFs including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtration on a single channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. The microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2011

High Level Requirements for the Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

The US Department of Energy, Office of Nuclear Energy (DOE-NE), has been tasked with the important mission of ensuring that nuclear energy remains a compelling and viable energy source in the U.S. The motivations behind this mission include cost-effectively meeting the expected increases in the power needs of the country, reducing carbon emissions and reducing dependence on foreign energy sources. In the near term, to ensure that nuclear power remains a key element of U.S. energy strategy and portfolio, the DOE-NE will be working with the nuclear industry to support safe and efficient operations of existing nuclear power plants. In the long term, to meet the increasing energy needs of the U.S., the DOE-NE will be investing in research and development (R&D) and working in concert with the nuclear industry to build and deploy new, safer and more efficient nuclear power plants. The safe and efficient operations of existing nuclear power plants and designing, licensing and deploying new reactor designs, however, will require focused R&D programs as well as the extensive use and leveraging of advanced modeling and simulation (M&S). M&S will play a key role in ensuring safe and efficient operations of existing and new nuclear reactors. The DOE-NE has been actively developing and promoting the use of advanced M&S in reactor design and analysis through its R&D programs, e.g., the Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Consortium for Advanced Simulation of Light Water Reactors (CASL) programs. Also, nuclear reactor vendors are already using CFD and CSM, for design, analysis, and licensing. However, these M&S tools cannot be used with confidence for nuclear reactor applications unless accompanied and supported by verification and validation (V&V) and uncertainty quantification (UQ) processes and procedures which provide quantitative measures of uncertainty for specific applications. The Nuclear Energy Knowledge base for Advanced Modeling and Simulation (NE-KAMS) is being developed at the Idaho National Laboratory in conjunction with Bettis Laboratory, Sandia National Laboratories, Argonne National Laboratory, Utah State University and others with the objective of establishing a comprehensive and web-accessible knowledge base that will provide technical services and resources for V&V and UQ of M&S in nuclear energy sciences and engineering. The knowledge base will serve as an important resource for technical exchange and collaboration that will enable credible and reliable computational models and simulations for application to nuclear reactor design, analysis and licensing. NE-KAMS will serve as a valuable resource for the nuclear industry, academia, the national laboratories, the U.S. Nuclear Regulatory Commission (NRC) and the public and will help ensure the safe, economical and reliable operation of existing and future nuclear reactors. From its inception, NE-KAMS will directly support nuclear energy research, development and demonstration programs within the U.S. Department of Energy (DOE), including the CASL, NEAMS, Light Water Reactor Sustainability (LWRS), Small Modular Reactors (SMR), and Next Generation Nuclear Power Plant (NGNP) programs. These programs all involve M&S of nuclear reactor systems, components and processes, and it is envisioned that NE-KAMS will help to coordinate and facilitate collaboration and sharing of resources and expertise for V&V and UQ across these programs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2018

NOS3: NASA Operational Simulator for Small Satellites

The NASA Operational Simulator for Small Satellites (NOS3) is a suite of open-source software tools to aid in areas such as software development, integration & test (I&T), mission operations/training, verification and validation (V&V), and software systems check-out. NOS3 provides a software development environment, a multi-target build system, operational interface/ground software, dynamics and environment simulations, and software-based hardware models. NOS3 has just recently been open-sourced by NASA and is available for immediate use. It enables the development of flight software (FSW) early in the project life cycle when hardware availability is limited. Small satellite development suffers from extensive lead times on many of the commercial-off-the-shelf (COTS) components as well as limited funding for engineering test units (ETUs). To alleviate the need to provide a hardware test-bed for each developer/tester, NOS3 hardware models are based upon characteristic data or manufacturer's data sheets for each individual component. The NOS3 hardware models' fidelity is such that FSW executes unaware that physical hardware is not present. This allows FSW binaries to be compiled for both the simulation environment and the flight computer without changing the FSW source code. For hardware models that provide data which is dependent upon the environment and spacecraft dynamics, such as a GPS receiver or magnetometer, an open-source tool from NASA GSFC (42 Spacecraft Simulator) is used to provide the necessary data. The underlying infrastructure used to transfer messages between FSW and the hardware models can also be used to monitor, intercept, and inject messages, which has proven to be beneficial for V&V of larger missions such as James Webb Space Telescope (JWST). As hardware is selected and becomes available, drivers can be added to the NOS3 environment to enable hardware-in-the-loop (HWIL) testing. When strict time synchronization is not vital, any number of combinations of hardware components and software-based models can be tested. NOS3 was actively used for FSW development and component testing of the Simulation-to-Flight 1 (STF-1) CubeSat and the Lunar IceCube CubeSat. As NOS3 matures, hardware models have been added for common small satellite components such as GPS receivers, electrical power systems and batteries, and antenna systems.

Suder, Mark↗

DOE OSTI2022

Thixotropic spectra and Ashby-style charts for thixotropy

There is no universal model for thixotropy, and comparing thixotropic effects between different fluids is a subtle yet challenging problem. We introduce a generalized (model-insensitive) framework for comparing thixotropic properties based on thixotropic spectra. A superposition of exponential stress modes distributed over thixotropic time scales is used to quantify buildup and breakdown times and mode strengths in response to step-change input. This mathematical framework is tested with several experimental step-shear rate data on colloidal suspensions. Low-dimensional metrics based on moments of the distribution reveal characteristic average thixotropic properties, which are visualized on Ashby-style diagrams. This method outlines a framework for describing thixotropy across a diverse range of microstructures, supporting scientific studies as well as material selection for engineering design applications.

Mechanics↗

DOE OSTI2010

Updated - Research Support Facility (RSF) construction time lapse

Haselden Construction and RNL built the 222,000 square-foot Research Support Facility (RSF) for the U.S. Department of Energy (DOE) on the National Renewable Energy Laboratory (NREL) campus. This time lapse video begins on July 23, 2009 and the last shot was taken in June 2010. The building is designed to be a model for sustainable, high-performance building design, and will provide DOE-owned work space for administrative staff who currently occupy leased space in the nearby Denver West Office Park. The engineers and scientists from NREL's Building Technology Program set the energy criteria and the energy design strategies that are making it possible for the RSF to use no more carbon-based energy than is produced by renewables. The RSF was designed by RNL. Stantec Consulting served as the project's engineering, energy modeling and sustainability consultant.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2010

NDARC - NASA Design and Analysis of Rotorcraft Validation and Demonstration

Validation and demonstration results from the development of the conceptual design tool NDARC (NASA Design and Analysis of Rotorcraft) are presented. The principal tasks of NDARC are to design a rotorcraft to satisfy specified design conditions and missions, and then analyze the performance of the aircraft for a set of off-design missions and point operating conditions. The aircraft chosen as NDARC development test cases are the UH-60A single main-rotor and tail-rotor helicopter, the CH-47D tandem helicopter, the XH-59A coaxial lift-offset helicopter, and the XV-15 tiltrotor. These aircraft were selected because flight performance data, a weight statement, detailed geometry information, and a correlated comprehensive analysis model are available for each. Validation consists of developing the NDARC models for these aircraft by using geometry and weight information, airframe wind tunnel test data, engine decks, rotor performance tests, and comprehensive analysis results; and then comparing the NDARC results for aircraft and component performance with flight test data. Based on the calibrated models, the capability of the code to size rotorcraft is explored.

Johnson, Wayne↗