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Thermal barrier coating life models developed under the NASA Lewis Research Center's Hot Section Technology (HOST) program are summarized. An initial laboratory model and three design-capable models are discussed. Current understanding of coating failure mechanisms are also summarized.
The rodent hindlimb unloading (HU) model was initially developed to simulate the cephalad fluid shift and musculoskeletal disuse in astronauts. Since then, the HU model has been applied to explore how other systems (e.g. immune, cardiovascular and CNS) respond to weightlessness. Most HU studies are performed with singly-housed animals, although social isolation also can substantially impact behavior and physiology, and therefore may confound HU experimental results. We hypothesized that relative to social housing, single housing exacerbates HU-induced dysfunction in select organ systems. We refined the standard NASA-Ames HU model to accommodate social housing in HU pairs, retaining advantageous features of traditional housing but using commercial off-the-shelf components to facilitate adoption by others. We conducted a 30 day HU experiment with adult, female C57Bl6/NJ mice that were either singly or socially housed. HU animals in both single and social HU housing displayed expected musculoskeletal deficits compared to housing matched, normally loaded (NL) controls. However, select immune, HPA axis, and CNS responses were differentially impacted by the HU social environment relative to NL controls. HU reduced % CD4+ T cells in singly-housed, but not socially-housed mice. Surprisingly, HU increased adrenal gland mass in socially-housed but not singly-housed mice, while social isolation increased adrenal gland mass in NL controls. HU also increased plasma corticosterone levels (day 30) in both singly and socially-housed mice. Thus, the social environment altered select adrenal and immune, but not musculoskeletal, responses to simulated weightlessness. We refine our original hypothesis since our results show combined stressors can mask, not only exacerbate, tissue responses to HU. These findings further expand the utility of the HU model for studying possible combined effects of the various spaceflight stressors.
After 39 years of continuous operation in space, the output of the Voyager 1 & 2 spacecraft Radioisotope Thermoelectric Generator (RTG) power systems has decreased to the point where managing the power margin and maintaining thermal control has become increasingly difficult. As the total power dissipation in the bus has decreased, propellant line temperatures and margin above minimum Allowable Flight Temperature (AFT) have decreased, creating risk of the hydrazine freezing (at 1.6°C). This is further complicated by the lack of existing thermal models that can be used to assess propellant tank and line temperatures. In 2014, an effort was begun to create a Voyager spacecraft thermal model for that purpose. A steady-state Thermal Desktop model has been created from scratch over the past two years. Applied Sciences Laboratory (ASL) started the initial thermal model development under contract to Jet Propulsion Laboratory (JPL). The effort relied primarily on archived manufacturing drawings, limited documentation, interviews of senior engineers who worked on the Voyager design and implementation, and the experience of the Voyager Flight Operations team. Data from the Voyager System Thermal Vacuum (STV) tests is no longer available, making it necessary to correlate the model to more recent flight data and small in-flight tests. Correlation was achieved to within ±5°C for a hot case and a cold case (both data sets from 2014). However, the flight system has very few temperature sensors directly on propellant lines. Therefore, the task remains to determine how best to use the model, in conjunction with flight data, to make sure the Voyagers can continue to fly successfully.
To model material ductile failure and crack propagation, cohesive zone elements can be embedded along potential fracture paths in a finite element simulation. When damage criteria are met, elements in the mesh decohere, simulating the formation and propagation of a crack. In this paper, we present a novel computational algorithm based on finite deformation theory, essential to modeling crack initiation and growth in solids undergoing large deformations. This new algorithm was formulated within a Lagrangian frame of reference to extend previous cohesive zone algorithms to include modeling crack growth in finite deformation contexts. The local coordinate system, necessary for defining an embedded cohesive zone, is constructed based upon the current configuration and is updated within the nonlinear iteration process, thereby resulting in the convergence of the solution for a growing crack in a large deformation quasi-static setting. The model’s accuracy was demonstrated by comparing finite element model simulation results with the analytic case of a constant surface separation, as shown in the verification examples. The power and efficacy of the algorithm to capture large deformations during crack growth were then demonstrated with a double cantilever beam example case. It indicates that the model can be applied to a variety of physical circumstances for predicting crack initiation and growth with delamination and fracture.
The Mechanical Threshold Stress (MTS) model provides excellent predictive capabilities for the material constitutive response for a wide range of temperatures and strain rates. However, the MTS model fails to capture the rapidly increasing yield stress at high strain rate behavior as the deformation controlling mechanism transitions from thermal activation to drag mechanisms, only capturing the linear behavior. Further, the model typically over predicts the flow stress behavior at yield and post yield due to its use of a constant work hardening rate parameter derived from the stress–strain response at constant saturation stress. An alternative approach to fitting portions of the MTS model is investigated and mathematical models are developed to address these issues. The results show that with appropriate experimental data, the mechanical threshold stress and work hardening rate parameters within the MTS model can quite easily and accurately be modified to extend applicability to high strain rate behavior and more accurately model the initial flow stress behavior at early work hardening rates without modification of the functions core to the MTS model itself.
As the development in flexible space structures expands, the need for an efficient and accurate suspension system for ground tests increases accordingly. In this article, a disk suspension system was developed. Analytical results describing the dynamics of a passive and active suspension system were generated given realistic parameters of the system. These results for the passive case, were then compared with the data obtained from an experimental model with initial displacement and random forcing inputs. The dynamics of the system was analyzed. Results show that the experimental model resembles closely the analytical model and therefore strongly suggests feasibility of such a suspension system.
BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.
A model that uses hindlimb unloading of rats was developed to study the consequences of skeletal unloading and reloading as occurs during and following space flight. Studies using the model were initiated two decades ago and further developed at National Aeronautics and Space Administration (NASA)-Ames Research Center. The model mimics some aspects of exposure to microgravity by removing weightbearing loads from the hindquarters and producing a cephalic fluid shift. Unlike space flight, the forelimbs remain loaded in the model, providing a useful internal control to distinguish between the local and systemic effects of hindlimb unloading. Rats that are hindlimb unloaded by tail traction gain weight at the same rate as pairfed controls, and glucocorticoid levels are not different from controls, suggesting that systemic stress is minimal. Unloaded bones display reductions in cancellous osteoblast number, cancellous mineral apposition rate, trabecular bone volume, cortical periosteal mineralization rate, total bone mass, calcium content, and maturation of bone mineral relative to controls. Subsequent studies reveal that these changes also occur in rats exposed to space flight. In hindlimb unloaded rats, bone formation rates and masses of unloaded bones decline relative to controls, while loaded bones do not change despite a transient reduction in serum 1,25-dihydroxyvitamin D (1,25D) concentrations. Studies using the model to evaluate potential countermeasures show that 1,25D, growth hormone, dietary calcium, alendronate, and muscle stimulation modify, but do not completely correct, the suppression of bone growth caused by unloading, whereas continuous infusion of transforming growth factor-beta2 or insulin-like growth factor-1 appears to protect against some of the bone changes caused by unloading. These results emphasize the importance of local as opposed to systemic factors in the skeletal response to unloading, and reveal the pivotal role that osteoblasts play in the response to gravitational loading. The hindlimb unloading model provides a unique opportunity to evaluate in detail the physiological and cellular mechanisms of the skeletal response to weightbearing loads, and has proven to be an effective model for space flight.
This paper describes the system engineering approach used to develop distributed multi-purpose simulations. The multi-purpose simulation architecture focuses on user needs, operations, flexibility, cost and maintenance. This approach was used to develop an International Space Station (ISS) simulator, which is called the International Space Station Integrated Simulation (ISIS)1. The ISIS runs unmodified ISS flight software, system models, and the astronaut command and control interface in an open system design that allows for rapid integration of multiple ISS models. The initial intent of ISIS was to provide a distributed system that allows access to ISS flight software and models for the creation, test, and validation of crew and ground controller procedures. This capability reduces the cost and scheduling issues associated with utilizing standalone simulators in fixed locations, and facilitates discovering unknowns and errors earlier in the development lifecycle. Since its inception, the flexible architecture of the ISIS has allowed its purpose to evolve to include ground operator system and display training, flight software modification testing, and as a realistic test bed for Exploration automation technology research and development.
Small DC-coupled battery test systems are deployed at NREL to evaluate capacity fade models and report on performance parameters such as round-trip efficiency under indoor and outdoor deployment scenarios. Initial commercial battery products include LG Chem RESU Lithium-ion and Avalon vanadium-redox flow batteries. Adapting indoor lab-scale test methods to outdoor systems has challenges, including maintaining constant temperature and fully controlling batteries through standard discharge curves. Initial measurements show the Lithium Ion battery systems performing within expectation, near 85% round-trip efficiency. Initial lifetime modeling and measurements indicate battery capacity may degrade by 20%-35% over 10 years.
Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.
This presentation will describe some initial results of paper-and-pencil studies of 4 or 5 application kernels applied to a processor-in-memory (PIM) system roughly similar to the Cascade Lightweight Processor (LWP). The application kernels are: * Linked list traversal * Sun of leaf nodes on a tree * Bitonic sort * Vector sum * Gaussian elimination The intent of this work is to guide and validate work on the Cascade project in the areas of compilers, simulators, and languages. We will first discuss the generic PIM structure. Then, we will explain the concepts needed to program a parallel PIM system (locality, threads, parcels). Next, we will present a simple PIM performance model that will be used in the remainder of the presentation. For each kernel, we will then present a set of codes, including codes for a single PIM node, and codes for multiple PIM nodes that move data to threads and move threads to data. These codes are written at a fairly low level, between assembly and C, but much closer to C than to assembly. For each code, we will present some hand-drafted timing forecasts, based on the simple PIM performance model. Finally, we will conclude by discussing what we have learned from this work, including what programming styles seem to work best, from the point-of-view of both expressiveness and performance.
Abstract. During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80 m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80 m wind speed MAE is reduced by 3 %–4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80 m wind speed MAE, up to 7 %–8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80 m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors.
This study was undertaken in MSFC's 14-Inch Trisonic Wind Tunnel to determine if rapid prototyping methods could be used in the design and manufacturing of high speed wind tunnel models in direct testing applications, and if these methods would reduce model design/fabrication time and cost while providing models of high enough fidelity to provide adequate aerodynamic data, and of sufficient strength to survive the test environment. Rapid prototyping methods utilized to construct wind tunnel models in a wing-body-tail configuration were: fused deposition method using both ABS plastic and PEEK as building materials, stereolithography using the photopolymer SL-5170, selective laser sintering using glass reinforced nylon, and laminated object manufacturing using plastic reinforced with glass and 'paper'. This study revealed good agreement between the SLA model, the metal model with an FDM-ABS nose, an SLA nose, and the metal model for most operating conditions, while the FDM-ABS data diverged at higher loading conditions. Data from the initial SLS model showed poor agreement due to problems in post-processing, resulting in a different configuration. A second SLS model was tested and showed relatively good agreement. It can be concluded that rapid prototyping models show promise in preliminary aerodynamic development studies at subsonic, transonic, and supersonic speeds.
We compute starburst models for M82, making use of recent theoretical tracks of stellar evolution. Detailed comparisons of our models and those of others demonstrate this technique to be quite reliable, with relatively little change in output parameters as a function of the selection of theoretical tracks or of estimates of the observational characteristics of the stars along these tracks. The models are matched to the observational constraints for M82 summarized by McLeod et al. (1993). The rate of star formation and time of observation were thoroughly optimized to produce the most favorable fit to the observations, but we still found that the recently proposed forms for the solar-neighborhood IMF cannot produce starbursts adequate to fit the observations of this galaxy. We then explored adjustments to the shape of the IMF to improve the fit to M82. We find (1) the shape of the IMF for high-mass stars need not be different from that observed locally; and (2) the most likely modification to the IMF in M82 is that stars with masses below a few solar masses form much less commonly than in the solar neighborhood.
Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a mechanical system that provides rapid and short-term support for patients with cardiac failure. In many patients, pulmonary function is also impaired, resulting in poorly-oxygenated cardiac outflow competing against well-oxygenated VA-ECMO outflow, a condition known as North-South syndrome. North-South syndrome is a primary concern because of its potential to cause cerebral hypoxia, which has a critical influence on neurological complications often seen in this patient population. In order to reduce ischemic neurological complications, it is important to understand how clinical decisions regarding VA-ECMO parameters influence blood oxygenation. In our work, we studied the impacts of flow rate and cannulation site on oxygenation using a one-dimensional (1D) model to simulate blood flow. Our model was initially tested by comparing blood flow results to those observed from experimental work in VA-ECMO patients. The 1D model was combined with a two-phase flow model to simulate oxygenation. Additionally, the influence of various other clinician-tunable parameters on oxygenation in the common carotid arteries (CCAs) were tested, including, blood viscosity, cannula position within the insertion artery, heart rate, and systemic vascular resistance (SVR), as well as geometrical changes such as arterial radius and length. Our results indicated that blood oxygenation to the brain strongly depended on the cannula insertion site and the VA-ECMO flow rate with a weaker but potentially significant dependence on arterial radius. During femoral cannulation, VA-ECMO flow rates greater than ~4.9 L/min were needed to perfuse the CCAs. However, axillary and central cannulation began to perfuse the CCAs at significantly lower flow (~1 L/min). These results may help explain the incidence of cerebral hypoxia in this patient population and the common need to change cannulation strategies during treatment to address this clinical problem. While this work describes patient-averaged results, determining these relationships between VA-ECMO parameters and cerebral hypoxia is an important step towards future work to develop patient-specific models that clinicians can use to improve outcomes.
The impact of surface roughness on flows over aerodynamically designed surfaces is of interested in a number of different fields. It has long been known the surface roughness will likely accelerate the laminar- turbulent transition process by creating additional disturbances in the boundary layer. However, there are very few tools available to predict the effects surface roughness will have on boundary layer flow. There are numerous implications of the premature appearance of a turbulent boundary layer. Increases in local skin friction, boundary layer thickness, and turbulent mixing can impact global flow properties compounding the effects of surface roughness. With this motivation, an investigation into the effects of surface roughness on boundary layer transition has been conducted. The effort involved both an extensive experimental campaign, and the development of a high fidelity roughness model implemented in a R ANS solver. Vast a mounts of experimental data was generated at the Texas A&M Oran W. Nicks Low Speed Wind Tunnel for the calibration and validation of the roughness model described in this work, as well as future efforts. The present work focuses on the development of the computational model including a description of the calibration process. The primary methodology presented introduces a scalar field variable and associated transport equation that interacts with a correlation based transition model. The additional equation allows for non-local effects of surface roughness to be accounted for downstream of rough wall sections while maintaining a "local" formulation. The scalar field is determined through a boundary condition function that has been calibrated to flat plate cases with sand grain roughness. The model was initially tested on a NACA 0012 airfoil with roughness strips applied to the leading edge. Further calibration of the roughness model was performed using results from the companion experimental study on a NACA 63 3 -418 airfoil. The refined model demonstrates favorable agreement predicting changes to the transition location, as well as drag, for a number of different leading edge roughness configurations on the NACA 63 3 -418 airfoil. Additional tests were conducted on a thicker S814 airfoil, with similar roughness configurations to the NACA 63 3 -418. Simulations run with the roughness model compare favorably with the results obtained in the experimental study for both airfoils.
A simple method is presented for using the daytime rise of the PBL height, combined with coincident satellite skin temperature measurements, to evaluate sensible heating and the effective surface roughness for heat transfer at synoptic locations. Multiple runs of a combination surface layer-mixed layer model are made in the central U.S., varying the values of surface moisture and roughness length around climatological means, and initializing the model with a set of atmospheric conditions from the synoptic report. The results, shown in figures and tables, are quite reasonable and spatially coherent, and depict well the sharp change in surface moisture and roughness which is known to take place across the central U.S.