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Under the NASA-KAIA-KARI ATM research collaboration agreement, SOSS ICN Model has been developed for Incheon International Airport. This presentation describes the model validation work in the project. The presentation will show the results and analysis of the validation.
The Human Research Program funded the development of the Integrated Medical Model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo simulation methodology, incorporating space flight and ground medical data, to estimate the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output, the IMM project team completed two validation studies that compared IMM predicted output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions. The validation study results showed that the IMM underpredicted the occurrence of ~10% of the modeled medical conditions for the STS missions and overpredicted ~20% of the modeled medical conditions for the ISS missions. These findings imply that the strength of IMM predictions to inform decisions depends on simulated mission specifications including length. This discrepancy could result from medical recording differences between ISS and STS that possibly influence observed incidence rates, IMM combining all "mission type" data as constant occurrence rate or fixed proportion across both mission types, misspecification of symptoms to conditions, and gaps in the literature informing the model. Some of these issues will be alleviated by updating the IMM source data through incorporation of the observed validation data.
The Human Research Program funded the development of the Integrated Medical Model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo simulation methodology, incorporating space flight and ground medical data, to estimate the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output, the IMM project team completed two validation studies that compared IMM predicted output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions. The validation study results showed that the IMM underpredicted the occurrence of ~10% of the modeled medical conditions for the STS missions and overpredicted ~20% of the modeled medical conditions for the ISS missions. These findings imply that the strength of IMM predictions to inform decisions depends on simulated mission specifications including length. This discrepancy could result from medical recording differences between ISS and STS that possibly influence observed incidence rates, IMM combining all "mission type" data as constant occurrence rate or fixed proportion across both mission types, misspecification of symptoms to conditions, and gaps in the literature informing the model. Some of these issues will be alleviated by updating the IMM source data through incorporation of the observed validation data.
The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpinning of those phenomenological laws have long been criticized as barriers to creating realistic models. In this work, geometric machine learning on graph data (e.g. finite element solutions) is used as a means to establish a connection between nonlinear dimensional reduction techniques and plasticity models. Geometric learning-based encoding on graphs allows the embedding of rich time-history data onto a low-dimensional Euclidean space such that the evolution of plastic deformation can be predicted in the embedded feature space. Finally, a corresponding decoder can then convert these low-dimensional internal variables back into a weighted graph such that the dominating topological features of plastic deformation can be observed and analyzed.
The HZETRN code has been identified by NASA for engineering design in the next phase of space exploration highlighting a return to the Moon in preparation for a Mars mission. In response, a new series of algorithms beginning with 2005 HZETRN, will be issued by correcting some prior limitations and improving control of propagated errors along with established code verification processes. Code validation processes will use new/improved low Earth orbit (LEO) environmental models with a recently improved International Space Station (ISS) shield model to validate computational models and procedures using measured data aboard ISS. These validated models will provide a basis for flight-testing the designs of future space vehicles and systems of the Constellation program in the LEO environment.
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The WetLab-2 system was developed by NASA Ames Research Center to offer new capabilities to researchers. The system can lyse cells and extract RNA (Ribonucleic Acid) on-orbit from different sample types ranging from microbial cultures to animal tissues. The purified RNA can then either be stabilized for return to Earth or can be used to conduct on-orbit quantitative Reverse Transcriptase PCR (Polymerase Chain Reaction) (qRT-PCR) analysis without the need for sample return. The qRT-PCR results can be downlinked to the ground a few hours after the completion of the run. The validation flight of the WetLab-2 system launched on SpaceX-8 on April 8, 2016. On orbit operations started on April 15th with system setup and was followed by three quantitative PCR runs using an E. coli genomic DNA template pre-loaded at three different concentrations. These runs were designed to discern if quantitative PCR functions correctly in microgravity and if the data is comparable to that from the ground control runs. The flight data showed no significant differences compared to the ground data though there was more variability in the values, this was likely due to the numerous small bubbles observed. The capability of the system to process samples and purify RNA was then validated using frozen samples prepared on the ground. The flight data for both E. coli and mouse liver clearly shows that RNA was successfully purified by our system. The E. coli qRT-PCR run showed successful singleplex, duplex and triplex capability. Data showed high variability in the resulting Cts (Cycle Thresholds [for the PCR]) likely due to bubble formation and insufficient mixing during the procedure run. The mouse liver qRT-PCR run had successful singleplex and duplex reactions and the variability was slightly better as the mixing operation was improved. The ability to purify and stabilize RNA and to conduct qRT-PCR on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. The ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. The WetLab-2 Project is supported by the Research Integration Office in the ISS Program.
The WetLab-2 system was developed by NASA Ames Research Center to offer new capabilities to researchers. The system can lyse cells and extract RNA (Ribonucleic Acid) on-orbit from different sample types ranging from microbial cultures to animal tissues. The purified RNA can then either be stabilized for return to Earth or can be used to conduct on-orbit quantitative Reverse Transcriptase PCR (Polymerase Chain Reaction) (qRT-PCR) analysis without the need for sample return. The qRT-PCR results can be downlinked to the ground a few hours after the completion of the run. The validation flight of the WetLab-2 system launched on SpaceX-8 on April 8, 2016. On orbit operations started on April 15th with system setup and was followed by three quantitative PCR runs using an E. coli genomic DNA template pre-loaded at three different concentrations. These runs were designed to discern if quantitative PCR functions correctly in microgravity and if the data is comparable to that from the ground control runs. The flight data showed no significant differences compared to the ground data though there was more variability in the values, this was likely due to the numerous small bubbles observed. The capability of the system to process samples and purify RNA was then validated using frozen samples prepared on the ground. The flight data for both E. coli and mouse liver clearly shows that RNA was successfully purified by our system. The E. coli qRT-PCR run showed successful singleplex, duplex and triplex capability. Data showed high variability in the resulting Cts (Cycle Thresholds [for the PCR]) likely due to bubble formation and insufficient mixing during the procedure run. The mouse liver qRT-PCR run had successful singleplex and duplex reactions and the variability was slightly better as the mixing operation was improved. The ability to purify and stabilize RNA and to conduct qRT-PCR on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. The ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. The WetLab-2 Project is supported by the Research Integration Office in the ISS Program.
The development, validation, and application of a general purpose multigrid solution algorithm and computer program for the computation of elliptic flows in complex geometries is presented. This computer program combines several desirable features including a curvilinear coordinate system, collocated arrangement of the variables, and Full Multi-Grid/Full Approximation Scheme (FMG/FAS). Provisions are made for the inclusion of embedded obstacles and baffles inside the flow domain. The momentum and continuity equations are solved in a decoupled manner and a pressure corrective equation is used to update the pressures such that the fluxes at the cell faces satisfy local mass continuity. Despite the computational overhead required in the restriction and prolongation phases of the multigrid cycling, the superior convergence results in reduced overall CPU time. The numerical scheme and selected results of several validation flows are presented. Finally, the procedure is applied to study the flowfield in a side-inlet dump combustor and twin jet impingement from a simulated aircraft fuselage.
NASA's Orion Crew Exploration Vehicle (CEV) will provide transportation for crew and cargo to and from destinations in support of the Constellation Architecture Design Reference Missions. Discrete Event Simulation (DES) is one of the design methods NASA employs for crew performance of the CEV. During the early development of the CEV, NASA and its prime Orion contractor Lockheed Martin (LM) strived to seek an effective low-cost method for developing and validating human performance DES models. This paper focuses on the method developed while creating a DES model for the CEV Rendezvous, Proximity Operations, and Docking (RPOD) task to the International Space Station. Our approach to validation was to attack the problem from several fronts. First, we began the development of the model early in the CEV design stage. Second, we adhered strictly to M&S development standards. Third, we involved the stakeholders, NASA astronauts, subject matter experts, and NASA's modeling and simulation development community throughout. Fourth, we applied standard and easy-to-conduct methods to ensure the model's accuracy. Lastly, we reviewed the data from an earlier human-in-the-loop RPOD simulation that had different objectives, which provided us an additional means to estimate the model's confidence level. The results revealed that a majority of the DES model was a reasonable representation of the current CEV design.
Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.
Here, this work develops a predictive density tool in Python, named Plutonium Nitrate Solutions (PuNS), to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer method and an empirical method were implemented into the PuNS tool to generate atom densities for use in MCNP6 material cards. These material cards are directly prepared into an MCNP6 input text file and are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, and plutonium isotope weight percentages. The PuNS tool is validated and verified against the International Criticality Safety Benchmark Evaluation Project Handbook experiments and is observed to predict densities within a root mean square error of 0.89% for the Pitzer method and 1.82% for the empirical method. These errors in density lead to up to 1569 pcm difference in MCNP6 calculated k eff for the Pitzer method and up to a 1751 pcm difference for the empirical method when compared to experimental benchmarks. Simultaneous work is also being performed at Los Alamos National Laboratory and the University of New Mexico to create a similar tool for plutonium chloride solutions, named Plutonium Chloride Solution, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also facilitate an improved understanding of solution systems and a potential relaxation in the conservatism of current aqueous plutonium processing criticality safety limits.
The PSEC5 ASIC is a high-speed waveform sampling chip designed for ultra-fast timing detectors, offering up to 40 GSPS sampling with 10-bit resolution. This makes it well-suited for applications requiring fine time resolution, such as MCPs and LGADs. This work focuses on the physical testing and validation of the chip s internal clocking and SPI-controlled registers. Testing began with inspection of schematics and the prototype to identify and resolve design issues. Then, custom firmware was developed for an Arduino controller to interface with the chip via SPI, enabling read and write access to key control registers. Results confirm that the VCO operates between ~3.2 4.0 GHz and remains stable under non-VCOVDD fluctuations. The Division Ratio register enables frequency division by known factors (256, 128, 64, etc.), indicating a pre-division frequency of 3.2 GHz when the digital band is unmodified. While most registers responded correctly, some issues were observed, including unexpected current draw and unstable discriminator behavior. Overall, the chip shows promising functionality, but further work is needed to understand the state of the read only registers and address the existing issues. Continued testing and firmware development will be critical to ensuring reliable integration into detector systems.
An attempt has been made to invert a large set of attenuation data for Love waves and toroidal oscillations in the earth, using a recent method by Backus and Gilbert. The difficulty in finding an acceptable model of internal friction which explains the data, under the assumption that the internal friction is independent of frequency, casts doubt on the validity of this assumption. A frequency-dependent model of internal friction is presented which is in good agreement with the seismic data and with recent experimental measurements of attenuation in rocks.
Surface and internal lava structures can be valid indicators of lava viscosity and rheology, provided that care is taken to identify and eliminate structures which are strain-rate-dependent. Here, a spectrum of types among Hawaiian basaltic flows is found ranging from pahoehoe to a'a, that are interpreted as marking a progression in lava viscosity and a change in rheology. The most fluid type in this spectrum is normal pahoehoe that has a smooth but commonly wrinkled or folded (ropy) surface. The next type, distinctly more viscous and probably non-Newtonian in rheology, is spiny pahoehoe which is characterized by a spinose surface and an absence of ropy structures. Preliminary studies on the long lavas of Mauna Loa indicated, perhaps surprisingly, that there is no clear-cut correlation of lava length with type in this spectrum of lavas, indicating that viscosity/yield strength of the basaltic lavas per se are not the primary controls determining flow length. Flowage of the lava through lava tubes, while it may help to account for the long flow distance of some lavas, is not a generally applicable explanation for long flow length.
Reaction rate data were collected for chemical reactions occurring at high temperatures during reentry of space vehicles. The principle of detailed balancing is used in modeling kinetics of chemical reactions at high temperatures. Although this principle does not hold for certain transient or incubation times in the initial phase of the reaction, it does seem to be valid for the rates of internal energy transitions that occur within molecules and atoms. That is, for every rate of transition within the internal energy states of atoms or molecules, there is an inverse rate that is related through an equilibrium expression involving the energy difference of the transition.
The Active Flexible Wing Project is a collaborative effort between the NASA Langley Research Center and Rockwell International. The objectives are the validation of methodologies associated with mathematical modeling, flutter suppression control law development and digital implementation of the control system for application to flexible aircraft. A flutter suppression control law synthesis for this project is described. The state-space mathematical model used for the synthesis included ten flexible modes, four control surface modes and rational function approximation of the doublet-lattice unsteady aerodynamics. The design steps involved developing the full-order optimal control laws, reducing the order of the control law, and optimizing the reduced-order control law in both the continuous and the discrete domains to minimize stochastic response. System robustness was improved using singular value constraints. An 8th order robust control law was designed to increase the symmetric flutter dynamic pressure by 100 percent. Preliminary results are provided and experiences gained are discussed.
The Active Flexible Wing Project is a collaborative effort between the NASA Langley Research Center and Rockwell International. The objectives are the validation of methodologies associated with mathematical modeling, flutter suppression control law development and digital implementation of the control system for application to flexible aircraft. A flutter suppression control law synthesis for this project is described. The state-space mathematical model used for the synthesis included ten flexible modes, four control surface modes and rational function approximation of the doublet-lattice unsteady aerodynamics. The design steps involved developing the full-order optimal control laws, reducing the order of the control law, and optimizing the reduced-order control law in both the continuous and the discrete domains to minimize stochastic response. System robustness was improved using singular value constraints. An 8th order robust control law was designed to increase the symmetric flutter dynamic pressure by 100 percent. Preliminary results are provided and experiences gained are discussed.