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

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At least 307 records · Page 17

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis

The NASA Eulerian Snow On Sea Ice Model (NESOSIM) is a new, open-source snow budget model that is currentlyconfigured to produce daily estimates of the depth and density of snow on sea ice across the Arctic Ocean throughthe accumulation season. NESOSIM has been developed in a three-dimensional Eulerian framework and includes two(vertical) snow layers and several simple parameterizations (accumulation, wind packing, advection_divergence, blowingsnow lost to leads) to represent key sources and sinks of snow on sea ice. The model is forced with daily inputs of snowfall and near-surface winds (from reanalyses), sea ice concentration (from satellite passive microwave data) and sea ice drift (from satellite feature tracking) during the accumulation season (August through April). In this study, we present the NESOSIM formulation, calibration efforts, sensitivity studies and validation efforts across an Arctic Ocean domain (100 km horizontal resolution). The simulated snow depth and density are calibrated with in situ data collected on drifting ice stations during the 1980s. NESOSIM shows strong agreement with the in situ seasonal cycles of snow depth and density, and shows good (moderate) agreement with the regional snow depth (density) distributions. NESOSIM is run for a contemporary period (2000 to 2015), with the results showing strong sensitivity to the reanalysis derived snowfall forcing data, with the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the Japanese Meteorological Agency 55-year reanalysis (JRA-55) forced snow depths generally higher than ERA-Interim,and the Arctic System Reanalysis (ASR) generally lower. We also generate and force NESOSIM with a consensus "median" daily snowfall dataset from these reanalyses.The results are compared against snow depth estimates derived from NASA's Operation IceBridge (OIB) snow radar data from 2009 to 2015, showing moderate_strong correlations and root mean squared errors of 10 cm depending on the OIB snow depth product analyzed, similar to the comparisons between OIB snow depths and the commonly used modified Warren snow depth climatology. Potential improvements to this initial NESOSIM formulation are discussed in the hopes of improving the accuracy and reliability of these simulated snow depths and densities.

Petty, Alek A.↗

Ventilation Heat Exchanger / Flow Meter for xPLSS

The flow meter / heat exchanger (FMHX) in the ventilation loop of the exploration EMU cools the ventilation gas and measures the ventilation flow rate. The heat exchanger transfers heat from the ventilation gas to the thermal control loop via a miniature shell-and-tube heat exchanger. The flow meters calculate the flow rate of gas through the ventilation loop based on the pressure drop across the heat exchanger core. Creare has delivered four design validation test (DVT) heat exchangers and five DVT flow meters to NASA JSC to support development of the exploration portable life support system (xPLSS). This paper describes the design and performance of the DVT units.The heat exchangers are designed to cool the ventilation gas to a specified temperature with low pressure losses under the most challenging operating conditions. The measured performance of the DVT heat exchangers agrees well with design models and meets all performance requirements. The flow meters use a MEMS thermal flow sensor to produce a signal that is proportional to a small bypass flow around the heat exchanger core. They are designed to achieve high measurement accuracy across the full range of xPLSS operating conditions. We calibrated the flow meters in a special-purpose flow facility that simulates operation in the xPLSS ventilation loop. Calibration testing shows that DVT flow meters produce digital output for vent loop mass flow that meets NASA’s accuracy requirements across the range of xPLSS operating conditions. This paper reviews the design of the heat exchangers and flow meters and presents data from the final flow meter calibration testing, heat exchanger performance validation, and initial ground testing in NASA’s xPLSS.

spacesuit↗

Ventilation Heat Exchanger / Flow Meter for xPLSS

The flow meter / heat exchanger (FMHX) in the ventilation loop of the exploration EMU cools the ventilation gas and measures the ventilation flow rate. The heat exchanger transfers heat from the ventilation gas to the thermal control loop via a miniature shell-and-tube heat exchanger. The flow meters calculate the flow rate of gas through the ventilation loop based on the pressure drop across the heat exchanger core. Creare has delivered four design validation test (DVT) heat exchangers and five DVT flow meters to NASA JSC to support development of the exploration portable life support system (xPLSS). This paper describes the design and performance of the DVT units.The heat exchangers are designed to cool the ventilation gas to a specified temperature with low pressure losses under the most challenging operating conditions. The measured performance of the DVT heat exchangers agrees well with design models and meets all performance requirements. The flow meters use a MEMS thermal flow sensor to produce a signal that is proportional to a small bypass flow around the heat exchanger core. They are designed to achieve high measurement accuracy across the full range of xPLSS operating conditions. We calibrated the flow meters in a special-purpose flow facility that simulates operation in the xPLSS ventilation loop. Calibration testing shows that DVT flow meters produce digital output for vent loop mass flow that meets NASA’s accuracy requirements across the range of xPLSS operating conditions. This paper reviews the design of the heat exchangers and flow meters and presents data from the final flow meter calibration testing, heat exchanger performance validation, and initial ground testing in NASA’s xPLSS.

spacesuit↗

An Imaging Calorimeter for Access-Concept Study

A mission concept study to define the "Advanced Cosmic-ray Composition Experiment for Space Station (ACCESS)" was sponsored by the National Aeronautics and Space Administration (NASA). The ACCESS instrument complement contains a transition radiation detector and an ionization calorimeter to measure tile spectrum of protons, helium, and heavier nuclei up to approximately 10(exp 15) eV to search for the limit of S/N shock wave acceleration, or evidence for other explanations of the spectra. Several calorimeter configurations have been studied, including the "baseline" totally active bismuth germanate instrument and sampling calorimeters utilizing various detectors. The Imaging Calorimeter for ACCESS (ICA) concept comprises a carbon target and a calorimeter using a high atomic number absorber sampled approximately each radiation length (rl) by thin scintillating fiber (SCIFI) detectors. The main features and options of the ICA instrument configuration are described in this paper. Since direct calibration is not possible over most of the energy range, the best approach must be decided from simulations of calorimeter performance extrapolated from CERN calibrations at 0.375 TeV. This paper presents results from the ICA simulations study.

Parnell, T. A.↗

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗

Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments

The Kennedy and O’Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its “knobs” (calibration inputs) to best match observations from a real physical/field experiment and correct for any modeling bias (second GP) when predicting under new field conditions (design inputs). There are well-established methods for placement of design inputs for data-efficient planning of a simulation campaign in isolation, that is, without field data: space-filling, or via criterion like minimum integrated mean-squared prediction error (IMSPE). Analogues within the coupled GP KOH framework are mostly absent from the literature. Here, in this study, we derive a closed form IMSPE criterion for sequentially acquiring new simulator data for KOH. We illustrate how acquisitions space-fill in design space, but concentrate in calibration space. Closed form IMSPE precipitates a closed-form gradient for efficient numerical optimization. We demonstrate that our KOH-IMSPE strategy leads to a more efficient simulation campaign on benchmark problems, and conclude with a showcase on an application to equilibrium concentrations of rare earth elements for a liquid–liquid extraction reaction.

97 MATHEMATICS AND COMPUTING↗

New technique for oil backstreaming contamination measurements

Due to the large size and the number of diffusion pumps, space simulation chambers cannot be easily calibrated by the usual test dome method for measuring backstreaming from oil diffusion pumps. In addition, location dependent contamination may be an important parameter of the test. The backstreaming contamination in the Space Power Facility (SPF) near Sandusky, Ohio, the largest space simulation vacuum test chamber in the U.S.A. was measured. Small size clean silicon wafers as contamination sensors placed at all desired measurement sites were used. The facility used diffusion pumps with DC 705 oil. The thickness of the contamination oil film was measured using ellipsometry. Since the oil did not wet uniformly the silicon substrate, two analysis models were developed to measure the oil film: continuous, homogeneous film and islands of oil with the islands varying in coverage fraction and height. In both cases, the contamination film refractive index was assumed to be that of DC 705. The second model improved the ellipsometric analysis quality parameter by up to two orders of magnitude, especially for the low coverage cases. Comparison of the two models for our case shows that the continuous film model overestimates the oil volume by less than 50 percent. Absolute numbers for backstreaming are in good agreement with published results for diffusion pumps. Good agreement was also found between the ellipsometric results and measurements done by x ray photoelectron spectroscopy (XPS) and by scanning electron microscopy (SEM) on samples exposed to the same vacuum runs.

Alterovitz, S. A.↗

A new technique for oil backstreaming contamination measurements

Due to the large size and the number of diffusion pumps, space simulation chambers cannot be easily calibrated by the usual test dome method for measuring backstreaming from oil diffusion pumps. In addition, location dependent contamination may be an important parameter of the test. The backstreaming contamination was measured in the Space Power Facility (SPF) near Sandusky, OH, the largest space simulation vacuum test chamber in the U.S.. Small clean silicon wafers placed at all desired measurement sites were used as contamination sensors. The facility used diffusion pumps with DC 705 oil. The thickness of the contamination oil film was measured using ellipsometry. Since the oil did not wet the silicon substrate uniformly, two analysis models were developed to measure the oil film: (1) continuous, homogeneous film; and (2) islands of oil with the islands varying in coverage fraction and height. In both cases, the contamination film refractive index was assumed to be that of DC 705. The second model improved the ellipsometric analysis quality parameter by up to two orders of magnitude, especially for the low coverage cases. Comparison of the two models shows that the continuous film model overestimates the oil volume by less than 50 percent. Absolute numbers for backstreaming are in good agreement with published results for diffusion pumps. Good agreement was also found between the ellipsometric results and measurements done by x-ray photoelectron spectroscopy (XPS) and by scanning electron microscopy (SEM) on examples exposed to the same vacuum runs.

Alterovitz, S. A.↗

An Overview of Experiments and Modeling of Polysiloxane-Coated Thermal Protection Systems for Missions to Mars, Titan, and Beyond.

Phenolic Impregnated Carbon Ablator (PICA) gained heritage during the historic Stardust mission, where it successfully returned samples from a comet’s tail and has since been instrumental in delivering payloads to the surface of Mars [1-3]. Most recently, PICA enabled the safe return of samples collected from asteroid Bennu as part of the OSIRIS-REx mission. This rich legacy underscores PICA’s critical role in allowing NASA’s most ambitious exploration missions. However, the friable nature of its phenolic phase presents challenges during handling and pre-launch activities. To mitigate this issue, PICA is coated with a polysiloxane resin system, which serves to suppress particulate dispersion and thereby safeguard spacecraft components. A comprehensive understanding of the polysiloxane resin’s behavior is imperative, as it profoundly shapes the material response of PICA during atmospheric entry by influencing its thermal and oxidative stability. This influence extends to thermocouple plugs embedded within thermal protection systems. These plugs have demonstrated their significance in missions such as Mars Science Laboratory (MSL) and Mars 2020, where the MEDLI and MEDLI2 instrumentation suites delivered in-valuable insights into the performance of thermal protection systems during entry into the Martian atmosphere [4]. Looking ahead, missions such as Dragonfly, set to descend into Titan’s dense atmosphere, aim to leverage advanced sensor technologies to further refine our understanding of thermal protection response [5]. Moreover, thermocouple plugs play an essential role in validating cutting-edge material response models, such as those pioneered under NASA’s Entry Systems Modeling Project (ESM), designed, in-part, to predict the operational integrity of thermal protection systems under the extreme stresses of atmospheric entry. To achieve these modeling goals, ground-based experiments are crucial to provide the foundational data necessary for developing and refining these predictive tools. To this end, an extensive test campaign was conducted at the Hypersonic Materials Environmental Test System (HyMETS) to investigate the high-temperature behavior of the polysiloxane resin in an air environment [6]. These experiments revealed critical phenomena, including the formation of a silicon oxycarbide layer that enhances oxidation resistance, moderates surface temperatures, and alters in-depth thermal response. Building on these findings, subsequent tests were designed to simulate atmospheric entry conditions in reactive gases, such as CO2 and N2, to mimic the environments of Mars and Titan, respectively, as well as non-reactive gases representing the atmospheres of the Ice Giants (Neptune and Uranus). A heating rate dependent decomposition mechanism has been identified for the polysiloxane resin under oxidizing conditions (Fig. 1). In the initial stage, the resin and the underlying thermal protection system undergo pyrolysis, rapidly generating a thin amorphous silicon oxycarbide interwoven with carbonaceous char and residual fibers from PICA. During the second stage, the nascent oxide layer establishes a robust, oxidation-resistant thermal barrier coating, which significantly impedes heat transfer to the underlying carbonaceous char, resulting in a stagnation of the surface temperature. A key factor contributing to this thermal resistance is the low recombination efficiency of atomic oxygen (γ), which further diminishes the heat load on the material’s interior layers [7]. Moreover, as the surface temperature stagnates, the silicon oxycarbide phase separates into distinct regions of silica and free graphite. Ultimately, when the heat flux reaches a critical threshold, a third stage is triggered, leading to the breakdown of the coating through carbothermal reduction, exposing the underlying char layer. This exposure leads to a dramatic surface temperature spike, driven by highly exothermic reactions between atomic oxygen and the char layer, further accelerating material degradation. A detailed mass and heat transfer model of PICA coated with polysiloxane resin was implemented in the Porous material Analysis Toolbox based on OpenFOAM, PATO [8]. The initial stage was considered negligible in this model because the resin decomposition occurs rapidly within a thin surface layer. Instead, the coating was directly considered as an oxygen-resistant thermal barrier coating. For the second stage, the thin amorphous silicon oxycarbide was treated as a pure silica surface to simplify the thermochemical behavior. The model ac-counts for surface equilibrium processes using representative elements of the coating-environment system. For the third stage, specific boundary conditions were developed to estimate the onset and progression of the coating removal. Two-dimensional material response simulations were conducted to compare uncoated and coated PICA using boundary conditions calibrated with HyMETS data. Fig. 2 illustrates that the simulations closely align with experimental data, successfully reproducing measured temperature profiles. This work will include the latest advancements in the coating model, including the calibration of recombination of atomic oxygen at the surface during the second phase. These simulated results will be further validated against additional CO2 data points from HyMETS, reinforcing the models’ predictive capabilities. These mechanisms and their effects on thermal protection systems, including thermochemical behavior and thermocouple probe performance in extreme environments, provide crucial insights for optimizing spacecraft designs that safeguard scientific payload and ensure mission success in future planetary exploration endeavors.

Active Oxidation↗

Orbiting lidar simulations. I - Aerosol and cloud measurements by an independent-wavelength technique

Aerosol and cloud measurements have been simulated for a Space Shuttle lidar. Expected errors - in signal, transmission, density, and calibration - are calculated algebraically and checked by simulating measurements and retrievals using random-number generators. By day, vertical structure is retrieved for tenuous clouds, Saharan aerosols, and boundary layer aerosols (at 0.53 and 1.06 micron) as well as strong volcanic stratospheric aerosols (at 0.53 micron). By night, all these constituents are retrieved plus upper tropospheric and stratospheric aerosols (at 1.06 micron), mesospheric aerosols (at 0.53 micron), and noctilucent clouds (at 1.06 and 0.53 micron). The vertical resolution was 0.1-0.5 km in the troposphere, 0.5-2.0 km above, except 0.25-1.0 km in the mesospheric cloud and aerosol layers; horizontal resolution was 100-2000 km.

Russell, P. B.↗

A Flight-Calibrated Methodology for Determination of Cassini Thruster On-Times for Reaction Wheel Biases

The Cassini spacecraft, the largest and most complex interplanetary spacecraft ever built, continues to undertake unique scientific observations of planet Saturn, Titan, Enceladus, and other moons of the ring world. In order to maintain a stable attitude during the course of its mission, this three-axis stabilized spacecraft uses two different control systems: the Reaction Control System (or RCS) and the Reaction Wheel Assembly (RWA) control system. In the course of its mission, Cassini performs numerous reaction wheel momentum biases (or unloads) using its reaction control thrusters. The use of the RCS thrusters often imparts undesired velocity changes (delta Vs) on the spacecraft and it is crucial for Cassini navigation and attitude control teams to be able to, quickly but accurately, predict the hydrazine usage and delta V vector in Earth Mean Equatorial (J2000) inertial coordinates for reaction wheel bias events, without actually having to spend time and resources simulating the event in a dynamic or hardware-in-the-loop simulation environments. The flight-calibrated methodology described in this paper, and the ground software developed thereof, are designed to provide the RCS thruster on-times, with acceptable accuracy and without any form of dynamic simulation, for reaction wheel biases, along with the hydrazine usage and the delta V in EME-2000 inertial frame.

Reaction Control System↗

Radiometric calibration of an airborne multispectral scanner

The absolute radiometric calibration of the NS001 Thematic Mapper Simulator reflective channels was examined based on laboratory tests and in-flight comparisons to ground measurements. The NS001 data are calibrated in-flight by reference to the NS001 internal integrating sphere source. This source's power supply or monitoring circuitry exhibited greater instability in-flight during 1988-1989 than in the laboratory. Extrapolating laboratory behavior to in-flight data resulted in 7-20 percent radiance errors relative to ground measurements and atmospheric modeling. Assuming constancy in the source's output between laboraotry and in-flight resulted in generally smaller errors. Upgrades to the source's power supply and monitoring circuitry in 1990 improved its in-flight stability, though in-flight ground reflectance based calibration tests have not yet been performed.

Markham, Brian L.↗

Design and Calibration of Autonomous Coherent Doppler Lidar for Space Missions

Developed a new algorithm for the simulation of three dimensional homogeneous turbulent velocity fields. For typical atmospheric conditions it is impossible to produce a simulated velocity field that simultaneously satisfy a given spatial correlation and the corresponding spatial spectrum because of spectral aliasing. The new algorithms produce a turbulent velocity field which has accurate spatial correlations which is required for performance predictions from space-based systems. Developed a new algorithm for extracting the spatial statistics of the atmospheric velocity field using coherent Doppler lidar. The performance of the algorithm was compared with past methods and the new algorithm produces useful results for space-based data, which was not possible before. Developed new methods for verification of the errors in ground-based and space-based Doppler lidar wind measurements. These new methods do not require independent in situ data. This is an important issue for the verification of space-based Doppler lidar measurements of the global wind field. The performance of the new algorithm was compared with past results for both space-based and ground-based operation. The new algorithm has the best performance and is the only algorithm that performed satisfactory for spacebased operation. The performance of coherent Doppler lidar for a space missions with various scanning geometries was determined using computer simulation which contained the effects of random instrumental velocity errors, wind shear, wind variability along the range-gate and from shot-to-shot, and random variations in atmospheric aerosol backscatter over the measurement volume. The bias in the velocity estimates was small and the accuracy in the is typically less than 0.5 m/s for high signal conditions. For a large number of shot per velocity estimate, the threshold signal level for acceptable estimates is proportional to the number of shots to the minus one half power. This agrees with previous results determined for ground-based measurements. The use of multi-element optical detectors for autonomous operation of coherent Doppler lidar was shown to be a very promising technique. Optimal detector geometries were determined by computer simulation of performance: for ground-based testing with a fixed calibration target and for space-based operation using the random surface returns. The effects of refractive turbulence on ground-based calibration of coherent Doppler lidar was determined by computer simulations and compared with theoretical predictions. New techniques were required to correctly predict performance for the focused beam geometry commonly used for verification of space-based operation. An improved velocity estimator was evaluated for space-based applications were signal shot measurements are used to produce vector wind measurements. This permits more accurate measurements when the signal level is not known a priori or not available from multiple shot measurements. The average Doppler lidar signal spectrum including the effects of velocity turbulence was derived and calculated. This permits new estimation algorithms for turbulence based on spectral estimates. In situ atmospheric measurements were conducted and analyzed using an instrumented kite-platform. This work helps provide the required in situ data for verification of Doppler lidar velocity statistics.

Frehlich, Rod G.↗

Ozonesonde Quality Assurance: JOSIE-SHADOZ (2017) and SHALLOTS (2018)

Ozonesonde data constitute a mainstay of satellite calibration and are used for climatologies and analysis of trends, especially in the lower stratosphere where satellites are most uncertain. The electrochemical-concentration cell (ECC) ozonesonde has been deployed at ~100 stations worldwide since the 1960s, with changes over time in manufacture and procedures, including details of the cell chemical solution and data processing. As a consequence, there are biases among different stations and discontinuities in profile timeseries from individual site records. Since 1996 the Jülich [Germany] Ozone Sonde Intercomparison Experiment (JOSIE) has periodically tested ozonesondes in a simulation chamber designated the World Calibration Centre for Ozonesondes by WMO. In October- November 2017 a JOSIE campaign evaluated the sondes and procedures used in SHADOZ (Southern Hemisphere Additional Ozonesondes), a 14-station tropical and subtropical network. A distinctive feature of the 2017 JOSIE was that the tests were conducted by operators from eight SHADOZ stations; Nairobi, Natal, Irene, Costa Rica, Paramaribo, Reunion, Hanoi, Kuala Lumpur. Experimental protocols and preliminary results for the SHADOZ sonde configurations, which represent most of those in use today, are described. SHADOZ stations that follow WMO-recommended protocols record total ozone within 3% of the JOSIE reference instrument. Instrument biases noted in prior JOSIE and field tests like BESOS (2004) were noted in JOSIE-2017, with maximum effect in the stratosphere. In June 2018 we organized a series of dual launches during the OWLETS II campaign in the Maryland and Chesapeake Bay area (SHALLOTS = SHADOZ-OWLETS ParaLLel Ozonesonde Test Study). Instrument and solution types were varied as in JOSIE-2017 and three radiosonde-ozonesonde variants were tested. An example of a parallel sampling in SHALLOTS, from a Greenbelt EnSCI-iMet sonde combination flown with the Wallops SPCLMS package, is illustrated in the Figure. The result was a range of biases but in general the instrument combination (EnSCI-iMet) deployed at 11 SHADOZ stations recorded ~5-10% less ozone in the stratosphere than the SPC ECC sonde flown with a Vaisala or LMS system. These 2017 and 2018 results and prior JOSIEs demonstrate that regular testing is essential to maintain best practices in ozonesonde operations and to ensure high-quality data for the ozone assessment communities.

Quality assurance↗

Arcjet Semi-Elliptic Nozzle Simulations and Validation in Support of TPS Testing

Much of the ground based testing of advanced thermal protection system (TPS) components for the X33 program is done in arc-heated wind tunnels such as those located in the Arc-Jet Complex at NASA Ames Research Center. These facilities are capable of simulating the high temperature, chemically reacting flow environment experienced by the vehicle during flight. This allows one to test critical design issues such as maximum reuse temperatures, seals, gaps, and increases in heating due to interfaces between different materials. Computational fluid dynamics (CFD) has evolved to the point where it now can be used in the vehicle design process for accurate and timely prediction of trajectory based aerothermal heating environments for re-entry vehicles. It can also be used for simulation of the flow environments in ground based facilities such as arcjets. By utilization of the same CFD code and solution methodology, the important differences between ground test and flight may be quantified. The goal of this paper is to utilize CFD to provide validated simulations of the flow environment in the NASA-Ames semi elliptic nozzle arcjet facilities. The validation of the ground simulations will come From comparison to existing calibration data. Specific tests in support of the X33 TPS test program will ilso be simulated. In this manner, the differences between the ground test simulation and the flight environment can be identified for a measure of ground test to flight traceability.

Loomis, Mark↗

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.

Ham, S W↗