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Calibration of any optical remote measurement is required in order to: 1) extract information directly from the measured spectral radiance, 2) compare measurements acquired at different times and from different regions, 3) compare measurements with measurements from other instruments, and 4) derive information from measurements using physically based computer models.
To reduce the uncertainties associated with estimating the biological effects of ionizing radiation in tissue, researchers rely on laboratory experiments in which mono-energetic, single specie beams are applied to cell cultures, insects, and small animals. To estimate the radiation effects on astronauts in deep space or low Earth orbit, who are exposed to mixed field broad spectrum radiation, these experimental results are extrapolated and combined with other data to produce radiation quality factors, radiation weighting factors, and other risk related quantities for humans. One way to reduce the uncertainty associated with such extrapolations is to utilize analysis tools that are applicable to both laboratory and space environments. The use of physical and computational body phantoms to predict radiation exposure and its effects is well established and a wide range of human and non-human phantoms are in use today. In this paper, a computational rat phantom is presented, as well as a description of the process through which that phantom has been coupled to existing radiation analysis tools. Sample results are presented for two space radiation environments.
This issue features an resource report on Jet Propulsion Laboratory and a special focus on advanced composites and plastics. It also contains articles on electronic components and circuits, electronic systems, physical sciences, computer programs, mechanics, machinery, manufacturing and fabrication, mathematics and information sciences, and life sciences. This issue also contains a supplement on federal laboratory test and measurements.
Topics include: special coverage on advanced composites, plastics and metals, electronic components and circuits, electronic systems, physical sciences, computer software, mechanics, machinery/automation, manufacturing/fabrication book and reports, and a special section of Electronics Tech Briefs.
Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.
There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on-site capability than either airship concept, and 2) the airship concepts can attain higher levels of energy collection and storage than the airplane concept; however, attaining these energy benefits requires adverse design trades of reduced performance (small airship) or excessive solar array area (large airship).
Engine Icing Performance loss: rollback, surge, flameout, and even internal engine damagePartial melting and refreeze of ice inside engine core (Mason et al., 2006). Ingestion of ice crystals and aggregates, mixed-phase droplets, or supercooled liquid dropletsNeed to better understand the conditions and properties that lead to engine icing.Simulation and analysis (physical and computational, and modeling)Test facilities (PSL, NRC, ...). Thermal and computational models and analysisProbesMultiple probes (aerothermal probes and ice cloud characterization probes and techniques). Total temperatureTraditional total temperature probes (vented forward facing)Heated total temperature probes (Goodyear). Rearward facing (developmental). Total temperature relevance. Thermal interaction between the icing cloud and air flow impinging particles contribute to kinetic heating effect (Gent et al., 2000). Measurement considerations Temperature sensor accuracy. Incomplete recovery of total temperature. Thermal surfaces (sources and sinks). Flow effects (viscous losses). Debris contamination, including icing and ice ingestion.
Flight qualification of space vehicles is markedly different from those typically employed for aircraft. The concept of an extensive flight test campaign for a space vehicle does not exist, and vehicle designers must look to alternative techniques for demonstrating robust and reliable performance of their vehicles prior to operational flight. A space vehicle may undergo only a handful of flight tests in its development cycle, with each flight representing a drastically different flight phase or flight configuration. For instance, NASA’s Space Launch System (SLS) launch vehicle and Orion spacecraft will only see a total of four flight demonstrations before flying a crew on its first operational mission, and each flight demonstrates a unique vehicle configuration and/or set of flight conditions. The SLS will be flown only one time before it becomes operational (Artemis 1). The Orion spacecraft Crew Module (CM) will have been tested twice, once on a Delta IV launch vehicle (Exploration Flight Test 1) and once as a fully integrated system with the SLS launch vehicle (Artemis 1). The Orion Launch abort system will have been tested twice, once in a pad abort scenario (Pad Abort 1) and once in an inflight abort scenario (Ascent Abort 2) on a modified Peacekeeper booster. Both of these latter tests involve only a boiler plate CM, not a functional Orion spacecraft. Thus, unlike aircraft, there is very little opportunity for engineers to assess and evaluate their preflight predictions. Instead, space vehicle designers rely on Monte Carlo flight simulations with detailed dispersions of predicted nominal flight behavior to determine how robust their design is to errors and uncertainties in the flight conditions their vehicle may encounter. These Monte Carlo analyses entail thousands of trajectory simulations to demonstrate that the vehicle can meet design requirements at a specified level of reliability. From an aerodynamics and aerothermodynamics perspective, these trajectory simulations are fueled by an extensive aerodynamic database that covers the complete range of expected flight conditions, vehicle configurations, and flight attitudes expected in a given mission. Today, these databases amount to a table of engineering parameters that can be quickly interrogated by the trajectory simulator. The aerodynamic and aerothermodynamic databases are assembled via a series of ground tests, empirical and analytical analysis, physics-based computational analysis, applicable past flight performance data, and in some cases, engineering judgment. These databases generally take years to assemble for a new space vehicle system and in the case of SLS/Orion, over a decade of test and analysis have been expended to develop the extensive databases required to cover the myriad of configurations and potential flight conditions required for the system. Recently, it has been proposed that Computational Fluid Dynamic (CFD) and computing capability may be reaching a point where it is foreseeable that CFD could be integrated directly into the production trajectory simulation tools used to design NASA’s space vehicles. To demonstrate this, NASA has embarked on two demonstrations of this type of capability, one where six degree of freedom flight trajectory simulation equations are embedded in an existing CFD solver and another where a production CFD solver is loosely coupled with a production trajectory simulation tool. These efforts represent an initial demonstration of a future approach to flight trajectory simulation, but they are a far cry from the capability required to perform a full-up CFD-in-the-loop Monte Carlo trajectory simulation. Therefore, this represents a viable grand challenge for computational methods addressing space vehicle design and development. The final paper/presentation will discuss the many hurdles, beyond simply raw computational power, to realizing this grand challenge and how they map directly to the CFD Vision 2030 ojectives. Among these are the wide range of flight conditions, including accelerating/decelerating flight, encountered by a space vehicle during launch and/or entry. The vehicle can also encounter numerous configuration changes, some of which can be quite drastic, during the course of its flight, so robust, automated geometry modeling, grid generation, and adaptation will play a huge role in reaching this goal. Multiply this by 1000’s of trajectory simulations occurring simultaneously in a given Monte Carlo analysis, and the problem readily scales to absorb virtually any size of supercomputer envisioned today. The concept of CFD-in-the-loop Monte Carlo trajectory simulation poses a formidable challenge for emerging and future computing systems, and it has the potential to shave years off the development cycle for aerodynamic and aerothermodynamic performance predictions as compared to today’s space vehicle design approach.
Rapid Aero Modeling (RAM) applied to wind tunnel testing, RAM-T, is an approach to efficiently and automatically obtain aerodynamic models during testing. The approach saves time and resources by responding to the demand for experimental efficiency and model fidelity. Motivation for this demand is more acute when investigating a class of vehicles categorized as Urban Air Mobility (UAM) aircraft where many features from both aircraft and rotorcraft are present. RAM-T provides a feedback loop around the test facility to guide the test toward high-fidelity, statistically rigorous aircraft models. The general RAM approach is applicable to computational or physical experiments. It combines concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. This paper presents results from tests conducted for development of an automated RAM-T technology. The results highlight some of the unique features of RAM applied to eVTOL configurations.
The current literature considers a CFD validation experiment synonymously with a particular type of wind tunnel test. By drawing on the experience of the authors, this paper makes a case for broadening the definition to include a more balanced and synergistic exploitation of computational and physical testing techniques. The concept of validation dialog is introduced which, together with technique verification, is considered a key enabler in the pursuit of an improved CFD predictive capability. An outline of a lifecycle for a CFD validation experiment is also proposed to consolidate the thinking. The result, it is reasoned, will encourage improved engagement with a broader range of stakeholders and wider recognition of the value of the outcomes of what might otherwise be considered studies of lesser importance. In turn, this is expected to encourage the adoption of more systematic approaches to complex problems, such that they are more readily broken down into smaller, more focused endeavors, while at the same time making such activities easier to fund.
Striving to keep up with the constantly changing environment, whether physical or computing, NASA Worldview’s interactive web mapping application continues to make improvements to ensure that avenues to near-real time imagery are quick, easy and accessible. This poster will explore recent additions to NASA Worldview and the Global Imagery Browse Services (GIBS) of near real-time imagery and imagery visualizations - from geostationary to flood mapping visualizations; improvements to access to imagery - from granule swath visualizations to vector interactions with fires and other types of vectors; and improvements to imagery discovery - from enhancements to the timeline to providing more ways to locate relevant imagery in the layer picker.
Artificial Immune System is a rapidly growing field of information processing and computing based upon immune inspired paradigns of nonlinear dynamics. This paper introduces stochastic models which mimic the phenomenology of basic functions of immune systems such as self-nonself discrimination, self-repair, predator-prey pursuit, and reproduction.
The Event Horizon Telescope (EHT) has released analyses of reconstructed images of horizon-scale millimeter emission near the supermassive black hole at the center of the M87 galaxy. Parts of the analyses made use of a large library of synthetic black hole images and spectra, which were produced using numerical general relativistic magnetohydrodynamics fluid simulations and polarized ray tracing. In this article, we describe the PATOKA pipeline, which was used to generate the Illinois contribution to the EHT simulation library. We begin by describing the relevant accretion systems and radiative processes. We then describe the details of the three numerical codes we use, iharm, ipole, and igrmonty, paying particular attention to differences between the current generation of the codes and the originally published versions. Finally, we provide a brief overview of simulated data as produced by PATOKA and conclude with a discussion of limitations and future directions.
Commercial supersonic aircraft are expected to produce considerably more noise during landing and take-off operations than existing subsonic aircraft. Establishing noise regulation is challenging because no examples of this aircraft type are currently flying. Existing aircraft noise prediction tools can be used, but the noise source models for these empirical tools are typically based on data from subsonic aircraft components. The present work documents a procedure for using physics-based computational tools to generate the propagating sound field radiating out the nacelle inlet. Although no analytical source modeling is demonstrated, these tools utilize measured data to compare the complex pressure for various propagating modes. The discrepancies found in applying the propagation tools to the subsonic inlet will be ascribed to calculations of supersonic inlets being used to update current empirical noise prediction tools.
Tissue Weight Relief (TWR) is a physiological condition observed in human spaceflight. It not only impacts the injury biomechanics of soft tissue but also the physiological responses of the cardiovascular system both due to fluid redistribution and the effect of tissue-related transmural pressure on the large venous blood vessels. Understanding the effects of tissue weight relief is especially important because of the role it may play in understanding the cause of Space Associated Neuro-Ocular Syndrome (SANS). SANS can be characterized by a number of ocular changes which reduce visual acuity and SANS related symptoms occur in up to 51% of astronauts. A prevailing theory for the causation of SANS is that of headward (cephalad) fluid shift and a prolonged increase of Intracranial Pressure (ICP) similar to intracranial hypertension, which is not fully supported by the experimental data or astronaut symptom reporting. However, it is still believed that SANS is caused by a pressure change in the eye and the surrounding tissues. It has been proposed that TWR plays a substantial role in affecting internal pressures and fluid shifts in microgravity. In this effort, two whole-body Finite Element (FE) models – Elemance and THUMS – are used to ascertain the microgravity-associated TWR of the musculature surrounding the lower body veins. Elemance and THUMS are physics-based computational models that have been validated and verified for several automotive and domestic applications, and as such, can simulate the relief of soft tissue weight due to changes in the gravitation vector. Specifically, the current effort modeled the transition of the gravitational vector from 1G to 0G, applied across the whole-body model in a supine position. For each 1G to 0G transition simulation, the lower body vein’s transmural pressure-time profile was extracted and averaged around the anterior portion of the thigh muscle. The ascertained transmural pressure changes from 1G to 0G transition are given in Figure 1 for the Elemance and the THUMS FE models. The transmural pressure changes of 10 mmHg and 21 mmHg are in the same order of magnitude as Lu’s value of 44 mmHg. It is to be noted that Lu implemented a 0D to 1D lumped parameter model and the Elemance and THUMS are 3D higher order computational models. This proof-of-concept approach demonstrates that TWR pressure can be adequately estimated with in silico techniques however, further in silico investigations need to be conducted to address the unique contributions to the transmural pressure from each of the computational models.
NASA created, validated, and applied a high fidelity simulation toolchain for noise prediction of a fan system for a near-term civilian supersonic aircraft engine. A high fidelity inlet and multistage fan design were acquired as the basis for physics based computational studies. The overall tone noise was computed, which was used to help improve empirical models of fan inlet noise for system analysis purposes. Additional insights were gained during the study of the fan installation details and these are shared in this paper. Both overall amplitudes and variations due to design details should be of interest to engineers tasked with designing quiet fan systems for supersonic commercial aircraft. The outlook for high-fidelity simulations of aft fan noise and installation effects will also be discussed.
NASA created, validated, and applied a high fidelity simulation toolchain for noise prediction of a fan system for a near-term civilian supersonic aircraft engine. A high fidelity inlet and multistage fan design were acquired as the basis for physics based computational studies. The overall tone noise was computed, which was used to help improve empirical models of fan inlet noise for system analysis purposes. Additional insights were gained during the study of the fan installation details and these are shared in this paper. Both overall amplitudes and variations due to design details should be of interest to engineers tasked with designing quiet fan systems for supersonic commercial aircraft. The outlook for high-fidelity simulations of aft fan noise and installation effects will also be discussed.
Soot formation is a complex dynamic and intermittent process determined by properties of the fuel, combustor design, and combustor operation. Although the major steps in soot formation (i.e., formation of precursors, inception, growth and evolution) are similar for a variety of carbonaceous fuels, applications, and operating conditions, it remains unclear when the temporal transition between these steps occurs. An engineering prediction tool coupled with computational fluid physics (CFD), therefore needs to accurately model all these complex steps. To develop such a model, we propose the time-history concept for understanding the time dependency of soot formation as a function of local properties (i.e., temperature, velocity, local fuel air ratio, etc.). We continue our previous work with modeling the DLR aero-combustor [1] with our updated in-house CFD code, Open National Combustion Code (OpenNCC), that now includes a Multiple Time-Scale Flamelet Progress Variable approach and a the semi-empirical two-equation soot model. We injected massless tracer particles upstream of the injector region of the combustor to collect time-history statistics of the solution variables. The correlations between the collected statistics with respect to the experimental soot volume fraction data showed that time-history effect of certain flow variables, including turbulent kinetic energy (TKE), and multiple species is indeed important for soot formation. We then conducted a time-history based correlation analysis to determine the key species and the concentration ranges critical for soot formation (C6H5-based nucleation, acetylene-based surface growth, and oxidation with OH and O2). Based on the time-history correlation coefficient (THCC) analysis, we propose possible modifications to improve the current two-equation model.