Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “In situ model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Integrated In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) connects individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. MATLAB was favorable to use as the main software integration tool due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of technologies, including but not limited to, the water processing Lunar Auger Dryer for ISRU (LADI) system and an oxygen extraction carbothermal reduction process. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing heater energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Efforts to update the MAIT tool are ongoing to accommodate and scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗
NASA NTRSDate not supplied

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Advanced efforts with advanced models will include examining multiple production targets to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗
NASA NTRSDate not supplied

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗
NASA NTRSDate not supplied

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗
NASA NTRS2011

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.

Gregg, Watson↗
NASA NTRS2020

Basin-Scale River Runoff Estimation from GRACE Gravity Satellites, Climate Models and In Situ Observations: a Case Study in the Amazon Basin

River runoff is estimated as a water budget residual using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage time series, ERA5 reanalysis data, and precipitation observations for January 2003 through December 2015 for the Obidos upstream drainage basin and for the entire Amazon basin. Estimated runoff based on the water budget agrees remarkably well with in situgauge observations at Obidos, especially at seasonal time scales, with nearly perfect phase agreementbut slightly larger seasonal amplitude. The discrepancy in the seasonal amplitude maybe attributed to underestimation of river gauge runoff during the wet season when water overflows the riverbanks. The ERA5 model appears to overestimate long-term mean evapotranspiration in the Amazon by ~2 cm/monthb ased on comparisons with precipitation and runoff observations. Using precipitation data based on satellites and gauge observations relative to gauge observations alone improved agreement between water budget runoff estimates and in situ runoff observations. Seasonal variations in ERA5 simulated runoff are about twice as large as those from in situobservations and show a large phase lag as well. Water budget based runoff for the entire Amazon (~ 7,200 km3averaged 29over the 13 yr period) is significantly larger than observed runoff (~5,700 km3) at notably larger than previous estimates for the entire Amazon. These differences may be partly related to submarine runoff from the Amazon basin that cannot be captured by surface gauges.

Jianli Chen↗
NASA NTRSDate not supplied

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA) Tool for Subsystem Integration into Full-Scale Architectures

In situ resource utilization (ISRU) is the practice of producing mission consumables from local lunar/planetary resources, thereby minimizing system launch mass requirements, mainly through the production of propellant fuel components and life support resources. Modeling full ISRU technology architectures significantly impacts the design and optimization of individual unit processes and facilitates their introduction into service with the Science Technology Mission Directorate (STMD) logistical planning and operation space. The Mission Analysis and Integration Tool (MAIT) is a modeling framework that connects individual ISRU subsystem models for the purposes of technology down select, scaling & optimization, and end-to-end process planning. The development project team seeks to address specific STMD capability gaps by simulating ISRU systems in MAIT. The goal is to produce system architectures for the Moon and Mars that are linked to Key Performance Parameters (KPP) and environmental requirements. To that end, the framework is adaptive, flexible, and suitable for collaboration among government, private sector, and international entities. Our approach currently provides conventional outputs, such as mass, power, and volume, to analyze whole system trade spaces. However, the framework was designed to validate current breadboard subsystems, simulate future process design capacity, and allow flexibility to any external developer-driven subsystem model that is in a state of evolution.

SE&I↗
NASA NTRS1994

In situ measurements of the NO2/NO ratio for testing atmospheric photochemical models

Simultaneous in situ measurements of NO2, NO, O3, ClO, pressure and temperature have been made for the first time, presenting a unique opportunity to test our current understanding of the photochemistry of the lower stratospere. Data were collected from several flights of the ER-2 aircraft at mid-latitudes in May 1993 during NASA's Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE). The daytime ratio of NO2/NO remains fairly constant at 19 km with a typical value of 0.68 and standard deviation of +/- 17. The ratio observations are compared with simple steady-state calculations based on laboratory-measured reaction rates and modeled NO2 photolysis rates. At each measurement point the daytime NO2/NO with its measurements uncertainty overlap the results of steady-state caculations and associated uncertainty. Possible sources of error are examined in both model and measurements. It is shown that more accurate laboratory determinations of the NO + 03 reaction rate and of the NO2 cross-sections in the 200-220 K temperature range characteristic of the lower stratosphere would allow for a more robust test of our knowledge of NO(X) phtochemistry by reducing significant sources if uncertainties in the interpretation of statospheric measurements.

Jaegle, L.↗
NASA NTRS1994

In Situ Measurements of the NO2/NO Ratio for Testing Atmospheric Photochemical Models

Simultaneous in situ measurements of NO2, NO, O3, ClO, pressure and temperature have been made for the first time, presenting a unique opportunity to test our current understanding of the photochemistry of the lower stratosphere. Data were collected from several flights of the ER-2 aircraft at mid-latitudes in May 1993 during NASA's Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE). The daytime ratio of NO2/NO remains fairly constant at 19 km with a typical value of 0.68 and standard deviation of +/- 0.17. The ratio observations are compared with simple steady-state calculations based on laboratory-measured reaction rates and modeled NO2 photolysis rates. At each measurement point the daytime NO2/NO with its measurement uncertainty overlap the results of steady-state calculations and associated uncertainty. However, over all the ER-2 flights examined, the model systematically overestimates the ratio by 40% on average. Possible sources of error are examined in both model and measurements. It is shown that more accurate laboratory determinations of the NO + O3 reaction rate and of the NO2 cross-sections in the 200-220 K temperature range characteristic of the lower stratosphere would allow for a more robust test of our knowledge of NO(x) photochemistry by reducing significant sources of uncertainties in the interpretation of stratospheric measurements. The present measurements are compared with earlier observations of the ratio at higher altitudes.

Jaegle, L.↗
NASA NTRS2008

Incorporating Satellite Time-Series Data into Modeling

In situ time series observations have provided a multi-decadal view of long-term changes in ocean biology. These observations are sufficiently reliable to enable discernment of even relatively small changes, and provide continuous information on a host of variables. Their key drawback is their limited domain. Satellite observations from ocean color sensors do not suffer the drawback of domain, and simultaneously view the global oceans. This attribute lends credence to their use in global and regional model validation and data assimilation. We focus on these applications using the NASA Ocean Biogeochemical Model. The enhancement of the satellite data using data assimilation is featured and the limitation of tongterm satellite data sets is also discussed.

Gregg, Watson↗
NASA NTRS2005

On the Origin of the Saturnian Satellite System: Did Iapetus Form In-Situ?

Current models of planet and satellite formation are marred by our lack of understanding regarding the turbulent state of accretion disks. According to the Rayleigh criterion, Keplerian disks are hydrodynamically stable. Indeed, it has been argued that a carefully designed Taylor Couette experiment shows stability in the case of positive radial gradients in specific angular momentum even for high Reynolds numbers [1], in agreement with numerical simulations which consistently show turbulence decay [2]. Other possible sources of turbulence may fail due to low ionization, may decay as the optical depth decreases due to dust coagulation, may involve unrealistic boundary conditions, or result in limited transport. The difficulty stems not only from the degree of turbulence, but also from the kind of turbulence, and whether it may be characterized by an alpha parameter.

Mosqueira, I.↗
NASA NTRS2018

The Ability of NASA's Meteoroid Engineering Model (MEM) 3 to Replicate in Situ Impact Data

Meteoroid environment models must describe the mass, directionality, velocity, and density distributions of meteoroids in order to correctly predict the rate at which meteoroids impact spacecraft. We present an updated version of NASA's Meteoroid Engineering Model (MEM) that better captures the correlation between directionality and velocity and incorporates a bulk density distribution. We compare the resulting model with the rate of large particle impacts seen on the Long Duration Exposure Facility (LDEF) and the Pegasus I and II satellites. Impact crater counts are modeled using two different ballistic limit equations (BLEs), one of which assumes a constant depth-to-diameter ratio and one of which yields depth-to-diameter ratios that depend on meteoroid speed and density. MEM agrees with the in situ crater record to within the range of values associated with different BLEs, but our preliminary analysis indicates that the level of agreement could be improved by reducing the strength of the toroidal meteoroid population and increasing the strength of the helion/antihelion and apex populations.

Moorhead, Althea↗
NASA NTRS2018

New Formation Models for the Kepler-36 System

Formation of the planets in the Kepler-36 system is modeled by detailed numerical simulations according to the core-nucleated accretion scenario. The standard model is updated to include the dissolution of accreting rocky planetesimals in the gaseous envelope of the planet, leading to substantial enrichment of the envelope mass in heavy elements and a non-uniform composition with depth. For Kepler-36 c, models involving in situ formation and models involving orbital migration are considered. The results are compared with standard formation models. The calculations include the formation (accretion) phase, as well as the subsequent cooling phase, up to the age of Kepler-36 (7 Gyr). During the latter phase, mass loss induced by stellar XUV radiation is included. In all cases, the results fit the measured mass, 7.84 M, and radius, 3.68 R, of Kepler-36 c. Two parameters are varied to obtain these fits: the disk solid surface density at the formation location, and the "efficiency" factor in the XUV mass loss rate. The updated models are hotter and therefore less dense in the silicate portion of the planet and in the overlying layers of H/He, as compared with standard models. The lower densities mean that only about half as much H/He is needed to be accreted to fit the present-day mass and radius constraints. For Kepler-36 b, an updated in situ calculation shows that the entire H/He envelope is lost, early in the cooling phase, in agreement with observation.

planets and satellites:formation↗
NASA NTRS1981

The role of in-situ measurements in scintillation modelling

It is shown that the conflicting equatorial scintillation observations obtained from greatly separated ground stations can be organized in the framework of a longitudinal variation of irregularity occurrence, given satellite-borne, in situ measurements of irregularity amplitude of the global F-region irregularity morphology's general features. High-inclination satellite data are used to delineate the morphological features of the polar cap by means of such a method. The lack of diurnal and magnetic control of the irregularity morphology within the low solar flux, northern winter polar cap distinguishes this region from the auroral oval regime. A polar-orbiting communication system sensitive to phase perturbations may observe large differences in the phase-to-amplitude scintillation ratio, as it traverses the auroral oval and proceeds into the polar cap, with its sun-aligned arc system.

Basu, S.↗
NASA NTRS1989

The POLAR code wake model - Comparison with in situ observations

Measurements made by the plasma diagnostics package during Spacelab 2 are discussed and compared with predictions made with the Air Force Geophysics Laboratory POLAR wake code. This code uses a complex geometric model of the orbiter and the self-similar solution of the expansion of a plasma into a vacuum as its model basis. Excellent qualitative and quantitative agreement is found at distances greater than about 30 m. At least to the first order, the model's approximations are justified.

Murphy, G.↗