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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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Multilevel Probit Regression for 3-Alternative Forced Choice Audibility Testing

A recent psychoacoustic test at NASA Langley generated a dataset of 3-alternative forced-choice responses for 40 subjects that measured the audibility of a tone complex in a shaped broadband masker. The task was completed by 4 subjects at a time in a small theatre-like environment using predetermined stimuli levels. These data were subject to 4 forms of probit regression: a “complete pooling” analysis in which all data from the test was fit with one curve, two forms of “no pooling” analyses in which subjects’ data were treated individually (using both packaged and custom software), and a “partial pooling” analysis in which multilevel-regression software fit both individual curves as well as population-level parameters at the same time. The results of the analyses are compared in terms of both individual- and population-level parameters. Partial pooling appears to give the most consistent results at both levels, as well as provide the most robustness among the packaged approaches (albeit with added complexity over single-level regression). These results are also contained in a recent NASA technical memorandum entitled “Comparisons of Analysis Methods Applied to Alternative Forced Choice Audibility Data.”

Psychoacoustics↗

Effect of thermal conditioning on the initiation threshold of secondary high‐explosives

While most performance metrics of high–explosive (HE) based devices like detonation velocity, detonation pressure, and energy output are expected to degrade over time, the evolution of initiation threshold appears less clear, with claims of both increasing and decreasing trends in threshold having been made in the literature. This work analyzes D–optimally designed sequential binary test data for a few thermally conditioned porous–powder and polymer–bonded HE initiator systems using a Bayesian likelihood method employing the probit regression model. Here we find that in most cases the initiation threshold decreases (i.e., sensitivity increases) upon accelerated thermal conditioning. However, such results are nuanced and influenced by factors like the contact area of initiating stimulus, HE characteristics like density and specific surface area, as well as possible thermally induced changes to other materials and interfaces involved.

36 MATERIALS SCIENCE↗

Comparing the reliability of related populations with the probability of agreement

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regression model. Note that supplementary materials including code, datasets, and added discussion are available online.

97 MATHEMATICS AND COMPUTING↗

Focused Assessment with Sonography for Trauma in weightlessness: a feasibility study

BACKGROUND: The Focused Assessment with Sonography for Trauma (FAST) examines for fluid in gravitationally dependent regions. There is no prior experience with this technique in weightlessness, such as on the International Space Station, where sonography is currently the only diagnostic imaging tool. STUDY DESIGN: A ground-based (1 g) porcine model for sonography was developed. We examined both the feasibility and the comparative performance of the FAST examination in parabolic flight. Sonographic detection and fluid behavior were evaluated in four animals during alternating weightlessness (0 g) and hypergravity (1.8 g) periods. During flight, boluses of fluid were incrementally introduced into the peritoneal cavity. Standardized sonographic windows were recorded. Postflight, the video recordings were divided into 169 20-second segments for subsequent interpretation by 12 blinded ultrasonography experts. Reviewers first decided whether a video segment was of sufficient diagnostic quality to analyze (determinate). Determinate segments were then analyzed as containing or not containing fluid. A probit regression model compared the probability of a positive fluid diagnosis to actual fluid levels (0 to 500 mL) under both 0-g and 1.8-g conditions. RESULTS: The in-flight sonographers found real-time scanning and interpretation technically similar to that of terrestrial conditions, as long as restraint was maintained. On blinded review, 80% of the recorded ultrasound segments were considered determinate. The best sensitivity for diagnosis in 0 g was found to be from the subhepatic space, with probability of a positive fluid diagnosis ranging from 9% (no fluid) to 51% (500 mL fluid). CONCLUSIONS: The FAST examination is technically feasible in weightlessness, and merits operational consideration for clinical contingencies in space.

NASA Discipline Life Sciences Technologies↗

Comparing Methods for Assessing Reliability Uncertainty Based on Pass/Fail Data Collected Over Time

In this paper, we compare statistical methods for analyzing pass/fail data collected over time; some methods are traditional and one (the RADAR or Rationale for Assessing Degradation Arriving at Random) was recently developed. These methods are used to provide uncertainty bounds on reliability. We make observations about the methods' assumptions and properties. Finally, we illustrate the differences between two traditional methods, logistic regression and Weibull failure time analysis, and the RADAR method using a numerical example.

97 MATHEMATICS AND COMPUTING↗

Parametric and Nonparametric Models of U.S. Cost Overruns for Nuclear Power Plants

This study presents new data-driven models to estimate the effect of capacity on the percentage of cost overruns in the United States for nuclear power plant construction projects before and after the Three Mile Island accident. Parametric and nonparametric models have been developed that describe the significant shifts in nuclear energy costs during the dynamic environment. Employing a contemporary descriptive methodology and a quantitative analysis, we furnish a comprehensive overview of the alterations in cost overrun distribution and show the changes observed in other pivotal metrics alongside cost overruns. Our emphasis lies in documenting the fluctuations in cost overruns alongside nuclear reactor capacity levels and the increase of the overnight capital costs to build nuclear reactors. Our results show that increasing the size of nuclear reactors is not a factor statistically significant to decrease the percentage of cost overruns, and the probit model results provide evidence that an increase in size increases the probability of having cost overruns larger than 100% (double the estimated cost). We also compare our findings to two other regions: Asia and Europe.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Panning for gold: Enhancing the precision of sensitivity test data

Sensitivity tests apply a range of stimulus values to experimental subjects and record binary responses in order to estimate the distribution of threshold values in the subject population, where thresholds delineate responses from nonresponses. In many applications, such as explosives engineering, individual tests are expensive and are conducted in small runs. Scarcity of data results in nonexistence of estimates, or estimates with low precision. Here, we discuss various methods, such as combining test runs, covariate analysis, and penalized maximum likelihood, for enhancing precision and “mining more gold” from expensive test results.

97 MATHEMATICS AND COMPUTING↗

Single toxin dose-response models revisited

The goal of this paper is to offer a rigorous analysis of the sigmoid shape single toxin dose-response relationship. The toxin efficacy function is introduced and four special points, including maximum toxin efficacy and inflection points, on the dose-response curve are defined. The special points define three phases of the toxin effect on mortality: (1) toxin concentrations smaller than the first inflection point or (2) larger then the second inflection point imply low mortality rate, and (3) concentrations between the first and the second inflection points imply high mortality rate. Probabilistic interpretation and mathematical analysis for each of the four models, Hill, logit, probit, and Weibull is provided. Two general model extensions are introduced: (1) the multi-target hit model that accounts for the existence of several vital receptors affected by the toxin, and (2) model with a nonzero mortality at zero concentration to account for natural mortality. Special attention is given to statistical estimation in the framework of the generalized linear model with the binomial dependent variable as the mortality count in each experiment, contrary to the widespread nonlinear regression treating the mortality rate as continuous variable. The models are illustrated using standard EPA Daphnia acute (48 h) toxicity tests with mortality as a function of NiCl or CuSO{sub 4} toxin. - Highlights: • The paper offers a rigorous study of a sigmoid dose-response relationship. • The concentration with highest mortality rate is rigorously defined. • A table with four special points for five morality curves is presented. • Two new sigmoid dose-response models have been introduced. • The generalized linear model is advocated for estimation of sigmoid dose-response relationship.

60 APPLIED LIFE SCIENCES↗

Development of Head Injury Assessment Reference Values Based on NASA Injury Modeling

NASA is developing a new capsule-based, crewed vehicle that will land in the ocean, and the space agency desires to reduce the risk of injury from impact during these landings. Because landing impact occurs for each flight and the crew might need to perform egress tasks, current injury assessment reference values (IARV) were deemed insufficient. Because NASCAR occupant restraint systems are more effective than the systems used to determine the current IARVs and are similar to NASA s proposed restraint system, an analysis of NASCAR impacts was performed to develop new IARVs that may be more relevant to NASA s context of vehicle landing operations. Head IARVs associated with race car impacts were investigated by completing a detailed analysis of all of the 2002-2008 NASCAR impact data. Specific inclusion and exclusion criteria were used to select 4071 impacts from the 4015 recorder files provided (each file could contain multiple impact events). Of the 4071 accepted impacts, 274 were selected for numerical simulation using a custom NASCAR restraint system and Humanetics Hybrid-III 50th percentile numerical dummy model in LS-DYNA. Injury had occurred in 32 of the 274 selected impacts, and 27 of those injuries involved the head. A majority of the head injuries were mild concussions with or without brief loss of consciousness. The 242 non-injury impacts were randomly selected and representative of the range of crash dynamics present in the total set of 4071 impacts. Head dynamics data (head translational acceleration, translational change in velocity, rotational acceleration, rotational velocity, HIC-15, HIC-36, and the Head 3ms clip) were filtered according to SAE J211 specifications and then transformed to a log scale. The probability of head injury was estimated using a separate logistic regression analysis for each log-transformed predictor candidate. Using the log transformation constrains the estimated probability of injury to become negligible as IARVs approach zero. For the parameters head translational acceleration, head translational velocity change, head rotational acceleration, HIC-15, and HIC-36, conservative values (in the lower 95% confidence interval) that gave rise to a 5% risk of any injury occurring were estimated as 40.0 G, 7.9 m/s, 2200 rad/s2, 98.4, and 77.4 respectively. Because NASA is interested in the consequence of any particular injury on the ability of the crew to perform egress tasks, the head injuries that occurred in the NASCAR dataset were classified according to a NASA-developed scale (Classes I - III) for operationally relevant injuries, which classifies injuries on the basis of their operational significance. Additional analysis of the data was performed to determine the probability of each injury class occurring, and this was estimated using an ordered probit model. For head translational acceleration, head translational velocity change, head rotational acceleration, head rotational velocity, HIC-36, and head 3ms clip, conservative values of IARVs that produced a 5% risk of Class II injury were estimated as 50.7 G, 9.5 m/s, 2863 rad/s2, 11.0 rad/s, 30.3, and 46.4 G respectively. The results indicate that head IARVs developed from the NASCAR dataset may be useful to protect crews during landing impact.

Somers, Jeffrey T.↗

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗