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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 1,387 records · Page 77

SU-F-T-139: Meeting the Challenges of Quality Control in the TOPAS Monte Carlo Simulation Toolkit for Proton Therapy

Purpose: Monte Carlo particle transport simulation (MC) codes have become important tools in proton therapy and biology, both for research and practice. TOPAS is an MC toolkit serving users worldwide (213 licensed users at 95 institutions in 21 countries). It provides unprecedented ease in 4D placement of geometry components, beam sources and scoring through its user-friendly and reproducible parameter file interface. Quality control (QC) of stochastic simulation software is inherently difficult, and the versatility of TOPAS introduces additional challenges. But QC is vital as the TOPAS development team implements new features, addresses user feedback and reacts to upgrades of underlying software (i.e. Geant4). Methods: Whenever code is committed to our repository, over 50 separate module tests are automatically triggered via a continuous integration service. They check that the various module options execute successfully and that their results are statistically consistent with previous reference values. Prior to each software release, longer end-to-end tests automatically validate TOPAS against experimental data and a TOPAS benchmark. These include simulating multiple properties of spread-out Bragg peaks, validating nuclear models, and searching for differences in patient simulations. Results: Continuous integration has proven effective in catching regressions at the time they are introduced, particularly when implementing new features that involve refactoring code (e.g. multithreading and ntuple output). Code coverage statistics highlight untested portions of code and guide development of new tests. The various end-to-end tests demonstrate that TOPAS accurately describes the physics of proton therapy within clinical tolerances. Conclusion: The TOPAS QC strategy of frequent short tests and pre-release long tests has led to a more reliable tool. However, the versatility of TOPAS makes it difficult to predict how users might combine different modules, and so QC ultimately remains a partnership between the developer and the user. This work was funded by National Cancer Institute grant R01 CA 140735.

60 APPLIED LIFE SCIENCES↗

Development of design, qualification, screening, and application requirements for plastic encapsulated solid-state devices for space applications

Test data were collected on 1035 plastic encapsulated devices and 75 hermetically scaled control group devices that were purchased from each of five different manufacturers in the categories of (1) low power Schottsky TTL (bipolar) digital circuits; (2) CMOS digital circuits; (3) operational amplifier linear circuits; and (4) NPN transistors. These parts were subjected to three different initial screening conditions, then to extended life testing, to determine any possible advantages or trends for any particular screen. Several tests were carried out in the areas of flammability testing, humidity testing, high pressure steam (auroclave) testing, and high temperature storage testing. Test results are presented. Procurement and application considerations for use of plastic encapsulated semiconductors are presented and a statistical analysis program written to study the log normal distributions resulting from life testing is concluded.

Source record↗

It's All Relative: A Validation of Radiation Quality Comparison Metrics

The difference between high-LET and low-LET radiation is quantified by a measure called relative biological effectiveness (RBE). RBE is defined as the ratio of the dose of a reference radiation to that of a test radiation to achieve the same effect level, and thus, is described either as an iso-effector dose-to-dose ratio. A single dose point is not sufficient to calculate an RBE value; therefore, studies with only one dose point usually calculate an effect-to-effect ratio. While not formally used in radiation protection, these iso-dose values may still be informative. Shuryak, et al 2017 investigated the use of an iso-dose metric termed "radiation effects ratio" (RER) and used both RBE and RER to estimate high-LET risks. To apply RBE or RER to risk prediction, the selected metric must be uniquely defined. That is, the calculated value must be consistent within a model given a constant set of constraints and assumptions, regardless of how effects are defined using statistical transformations from raw endpoint data. We first test the RBE and the RER to determine whether they are uniquely defined using transformations applied to raw data. Then, we test whether both metrics can predict heavy ion response data after simulated effect size scaling between human populations or when converting animal to human endpoints.

Chappell, Lori J.↗

Multifamily Envelope Leakage Model

The objective of the 2013 research project was to develop the model for predicting fully guarded test results (FGT), using unguarded test data and specific building features of apartment units. The model developed has a coefficient of determination R2 value of 0.53 with a root mean square error (RMSE) of 0.13. Both statistical metrics indicate that the model is relatively strong. When tested against data that was not included in the development of the model, prediction accuracy was within 19%, which is reasonable given that seasonal differences in blower door measurements can vary by as much as 25%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building America Case Study: Predicting Envelope Leakage in Attached Dwellings (Fact Sheet)

'The cost for blower testing is high, because it is labor intensive, and it may disrupt occupants in multiple units. This high cost and disruption deters program participants, and dissuades them from pursuing energy improvements that would trigger air leakage testing, such as improvements to the building envelope.' This statement found in a 2012 report by Heschong Mahone Group emphasizes the importance of reducing the cost and complexity of blower testing in multifamily buildings. Energy efficiency opportunities are being bypassed. The cost of single blower testing is on the order of $300. The cost for guarded blower door testing, the more appropriate test for assessing energy savings opportunities, could easily be six times that and that's only if you have the equipment and simultaneous access to multiple apartments. Thus, the proper test is simply not performed. The objective of the 2013 research project was to develop the model for predicting fully guarded test results (FGT), using unguarded test data and specific building features of apartment units. The model developed has a coefficient of determination R2 value of 0.53 with a root mean square error (RMSE) of 0.13. Both statistical metrics indicate that the model is relatively strong. When tested against data that was not included in the development of the model, prediction accuracy was within 19%, which is reasonable given that seasonal differences in blower door measurements can vary by as much as 25%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗

Measuring the Weibull modulus of microscope slides

The objectives are that students will understand why a three-point bending test is used for ceramic specimens, learn how Weibull statistics are used to measure the strength of brittle materials, and appreciate the amount of variation in the strength of brittle materials with low Weibull modulus. They will understand how the modulus of rupture is used to represent the strength of specimens in a three-point bend test. In addition, students will learn that a logarithmic transformation can be used to convert an exponent into the slope of a straight line. The experimental procedures are explained.

Sorensen, Carl D.↗

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Parsons, David S.↗

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Parsons, David S.↗

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to shock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to shock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite shock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to shock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and shock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to shock induced loading.

Parsons, David↗

Experiment K-7-23: Effect of Spaceflight on Level and Function of Immune Cells: Proliferation and Cytokines - Part 2

Lymphocytes from the superficial inguinal lymph nodes of rats flown on the Cosmos 2044 space mission were tested for proliferation in response to polyclonal activators. Cells were cultured with T or B cell mitogens, phorbol ester and calcium ionophore, or T cell mitogen and the lymphokines interleukin-1 (IL-1) or interleukin-2 (IL-2), and assayed for DNA synthesis by (3)H-thymidine incorporation. Lymphocytes also were incubated with concanavalin A (Con A), a T cell mitogen, and tested for IL-2 production. Mitogen-stimulated proliferation of lymphocytes from rats exposed to microgravity was not significantly different from synchronous or vivarium controls. Responses to Con A and IL-2, and Con A and IL-1 likewise were unaffected by space flight. Lymphocytes from all of these groups responded well to phorbol ester and calcium ionophore stimulation. Furthermore, lymph node cells (LNC) from control rats and rats flown on Cosmos 2044 produced similar amounts of IL-2. The results obtained using hindlimb suspended rats were notably different from those of flight and control animals. LNC from suspended rats generally had greater proliferative responses to T cell mitogens than did lymphocytes from other groups. Responsiveness to a B cell mitogen was not enhanced. Con A-stimulated LNC from hindlimb suspended rats also produced more IL-2 than did lymphocytes from the other groups. This difference was statistically significant at both IL-2 induction times tested.

Nash, P. V.↗

Investigation of Error Patterns in Geographical Databases

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Dryer, David↗

A Framework for the Analysis of Deep Neural Networks in Autonomous Aerospace Applications using Bayesian Statistics

Deep Neural Networks (DNNs) are considered to be key components in many autonomous systems. Applications range from vision-based obstacle avoidance to intelligent/learning control and planning. Safety-critical applications as found in the aerospace domain require that the behavior of the DNN is validated and tested rigorously for safety of the autonomous system (AUS). In this paper, we present a framework to support testing of DNNs and the analysis of the network structure. Our framework employs techniques from statistical modeling and active learning to effectively generate test cases for DNN safety testing and performance analysis. We will present results of a case study on a physics-based Deep recurrent residual neural network (DR-RNN), which has been trained to emulate the aerodynamics behavior of a fixed-wing aircraft.

Deep Neural networks↗

Taguchi statistical design and analysis of cleaning methods for spacecraft materials

In this study, we have extensively tested various cleaning protocols. The variant parameters included the type and concentration of solvent, type of wipe, pretreatment conditions, and various rinsing systems. Taguchi statistical method was used to design and evaluate various cleaning conditions on ten common spacecraft materials.

Taguchi cleaning spacecraft materials↗

Service Life Extension of the Propulsion System of Long-Term Manned Orbital Stations

One of the critical non-replaceable systems of a long-term manned orbital station is the propulsion system. Since the propulsion system operates beginning with the launch of station elements into orbit, its service life determines the service life of the station overall. Weighing almost a million pounds, the International Space Station (ISS) is about four times as large as the Russian space station Mir and about five times as large as the U.S. Skylab. Constructed over a span of more than a decade with the help of over 100 space flights, elements and modules of the ISS provide more research space than any spacecraft ever built. Originally envisaged for a service life of fifteen years, this Earth orbiting laboratory has been in orbit since 1998. Some elements that have been launched later in the assembly sequence were not yet built when the first elements were placed in orbit. Hence, some of the early modules that were launched at the inception of the program were already nearing the end of their design life when the ISS was finally ready and operational. To maximize the return on global investments on ISS, it is essential for the valuable research on ISS to continue as long as the station can be sustained safely in orbit. This paper describes the work performed to extend the service life of the ISS propulsion system. A system comprises of many components with varying failure rates. Reliability of a system is the probability that it will perform its intended function under encountered operating conditions, for a specified period of time. As we are interested in finding out how reliable a system would be in the future, reliability expressed as a function of time provides valuable insight. In a hypothetical bathtub shaped failure rate curve, the failure rate, defined as the number of failures per unit time that a currently healthy component will suffer in a given future time interval, decreases during infant-mortality period, stays nearly constant during the service life and increases at the end when the design service life ends and wear-out phase begins. However, the component failure rates do not remain constant over the entire cycle life. The failure rate depends on various factors such as design complexity, current age of the component, operating conditions, severity of environmental stress factors, etc. Development, qualification and acceptance test processes provide rigorous screening of components to weed out imperfections that might otherwise cause infant mortality failures. If sufficient samples are tested to failure, the failure time versus failure quantity can be analyzed statistically to develop a failure probability distribution function (PDF), a statistical model of the probability of failure versus time. Driven by cost and schedule constraints however, spacecraft components are generally not tested in large numbers. Uncertainties in failure rate and remaining life estimates increase when fewer units are tested. To account for this, spacecraft operators prefer to limit useful operations to a period shorter than the maximum demonstrated service life of the weakest component. Running each component to its failure to determine the maximum possible service life of a system can become overly expensive and impractical. Spacecraft operators therefore, specify the required service life and an acceptable factor of safety (FOS). The designers use these requirements to limit the life test duration. Midway through the design life, when benefits justify additional investments, supplementary life test may be performed to demonstrate the capability to safely extend the service life of the system. An innovative approach is required to evaluate the entire system, without having to go through an elaborate test program of propulsion system elements. Evaluating every component through a brute force test program would be a cost prohibitive and time consuming endeavor. ISS propulsion system components were designed and built decades ago. There are no representative ground test articles for some of the components. A 'test everything' approach would require manufacturing new test articles. The paper outlines some of the techniques used for selective testing, by way of cherry picking candidate components based on failure mode effects analysis, system level impacts, hazard analysis, etc. The type of testing required for extending the service life depends on the design and criticality of the component, failure modes and failure mechanisms, life cycle margin provided by the original certification, operational and environmental stresses encountered, etc. When specific failure mechanism being considered and the underlying relationship of that mode to the stresses provided in the test can be correlated by supporting analysis, time and effort required for conducting life extension testing can be significantly reduced. Exposure to corrosive propellants over long periods of time, for instance, lead to specific failure mechanisms in several components used in the propulsion system. Using Arrhenius model, which is tied to chemically dependent failure mechanisms such as corrosion or chemical reactions, it is possible to subject carefully selected test articles to accelerated life test. Arrhenius model reflects the proportional relationship between time to failure of a component and the exponential of the inverse of absolute temperature acting on the component. The acceleration factor is used to perform tests at higher stresses that allow direct correlation between the times to failure at a high test temperature to the temperatures to be expected in actual use. As long as the temperatures are such that new failure mechanisms are not introduced, this becomes a very useful method for testing to failure a relatively small sample of items for a much shorter amount of time. In this article, based on the example of the propulsion system of the first ISS module Zarya, theoretical approaches and practical activities of extending the service life of the propulsion system are reviewed with the goal of determining the maximum duration of its safe operation.

Kamath, Ulhas↗

Lubricant and additive effects on spur gear fatigue life

Spur gear endurance tests were conducted with six lubricants using a single lot of consumable-electrode vacuum melted (CVM) AISI 9310 spur gears. The sixth lubricant was divided into four batches each of which had a different additive content. Lubricants tested with a phosphorus-type load carrying additive showed a statistically significant improvement in life over lubricants without this type of additive. The presence of sulfur type antiwear additives in the lubricant did not appear to affect the surface fatigue life of the gears. No statistical difference in life was produced with those lubricants of different base stocks but with similar viscosity, pressure-viscosity coefficients and antiwear additives. Gears tested with a 0.1 wt % sulfur and 0.1 wt % phosphorus EP additives in the lubricant had reactive films that were 200 to 400 (0.8 to 1.6 microns) thick.

Townsend, D. P.↗

Lubricant and additive effects on spur gear fatigue life

Spur gear endurance tests were conducted with six lubricants using a single lot of consumable-electrode vacuum melted (CVM) AISI 9310 spur gears. The sixth lubricants was divided into four batches each of which had a different additive content. Lubricant tested with a phosphorus-type load carrying additive showed a statistically significant improvement in life over lubricants without this type of additive. The presence of sulfur type antiwear additives in the lubricant did not appear to affect the surface fatigue life of the gears. No statistical difference in life was produced with those lubricants of different base stocks but with similar viscosity, pressure-viscosity coefficients and antiwar additives. Gears tested with a 0.1 wt pct sulfur and 0.1 wt pct phosphorus EP additives in the lubricant had reactive films that were 200 to 400 (0.8 to 1.6 microns) thick.

Townsend, D. P.↗

Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events

The Weather Risk Attribution Forecast (WRAF) is a forecasting tool that uses output from global climate models to make simultaneous attribution statements about whether and how greenhouse gas emissions have contributed to extreme weather across the globe. However, in conducting a large number of simultaneous hypothesis tests, the WRAF is prone to identifying false “discoveries.” A common technique for addressing this multiple testing problem is to adjust the procedure in a way that controls the proportion of true null hypotheses that are incorrectly rejected, or the false discovery rate (FDR). Unfortunately, generic FDR procedures suffer from low power when the hypotheses are dependent, and techniques designed to account for dependence are sensitive to misspecification of the underlying statistical model. In this paper, we develop a Bayesian decision-theoretical approach for dependent multiple testing and a nonparametric hierarchical statistical model that flexibly controls false discovery and is robust to model misspecification. We illustrate the robustness of our procedure to model error with a simulation study, using a framework that accounts for generic spatial dependence and allows the practitioner to flexibly specify the decision criteria. Finally, we apply our procedure to several seasonal forecasts and discuss implementation for the WRAF workflow. Lastly, supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

54 ENVIRONMENTAL SCIENCES↗