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Goodenow, D.

Publications and source records attributed to Goodenow, D..

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Introduction to Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT)

A key component in the development of NASA Human Research Programs (HRP) next generation risk model, the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) intends to deliver a means to quantify how HRP products impact astronaut medical and health risks. MEDPRAT is extensible to the majority of exploration missions. Similar to other risk models, the tool utilizes the available space and terrestrial medical data. MEDPRAT is designed to be extended with additional human health research information, medical equipment, space and terrestrial standards and practices to assess space flight medical risk in a manner consistent with other risk measures used in spacecraft and mission design. This tool provides risk-based medical system design information necessary to evaluate new technologies, procedures, research insights and mission plans.

physiological response↗
NASA NTRS2018

Sensitivity Analysis of the Change of Renal Stone Occurrence Rates in Astronauts Using Urine Chemistries

Changes in urine chemistry, during and post-flight, potentially alter the likelihood of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidences of renal stones in US astronauts exist and the question How much does this risk change with space flight? remains difficult to accurately quantify. Previous work by our group has illustrated the application of multi-factor deterministic and probabilistic modeling to assess the change in predicted likelihood of renal stone. Utilizing 1517 astronaut urine chemistries to inform the renal stone occurrence rate forecasting model, we performed a sensitivity analysis on urine chemistry components for their influence on predictions of renal stone size and rate of renal stone occurrence.

physiological response↗
NASA NTRS2016

Forecasting the Change of Renal Stone Occurrence Rates in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidences of renal stones in US astronauts exists and the question How much does this risk change with space flight? remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone occurrence.

physiological response↗
NASA NTRS2016

Effect of Dietary Countermeasures and Impact of Gravity on Renal Calculi Size Distributions Predicted by PBE-System and PBE-CFD Models

Renal stone disease is not only a concern on earth but can conceivably pose a serious risk to the astronauts health and safety in Space. In this work, two different deterministic models based on a Population Balance Equation (PBE) analysis of renal stone formation are developed to assess the risks of critical renal stone incidence for astronauts during space travel. In the first model, the nephron is treated as a continuous mixed suspension mixed product removal crystallizer and the PBE for the nucleating, growing and agglomerating renal calculi is coupled to speciation calculations performed by JESS. Predictions of stone size distributions in the kidney using this model indicate that the astronaut in microgravity is at noticeably greater but still subcritical risk and recommend administration of citrate and augmented hydration as effective means of minimizing and containing this risk. In the second model, the PBE analysis is coupled to a Computational Fluid Dynamics (CFD) model for flow of urine and transport of Calcium and Oxalate in the nephron to predict the impact of gravity on the stone size distributions. Results presented for realistic 3D tubule and collecting duct geometries, clearly indicate that agglomeration is the primary mode of size enhancement in both 1g and microgravity. 3D numerical simulations seem to further indicate that there will be an increased number of smaller stones developed in microgravity that will likely pass through the nephron in the absence of wall adhesion. However, upon reentry to a 1g (Earth) or 38g (Mars) partial gravitational fields, the renal calculi can lag behind the urinary flow in tubules that are adversely oriented with respect to the gravitational field and grow agglomerate to large sizes that are sedimented near the wall with increased propensity for wall adhesion, plaque formation, and risk to the astronauts.

Renal Stones↗
NASA NTRS2016

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

Probability Theory↗
NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗
NASA NTRS2015

Integrated Medical Model Project - Overview and Summary of Historical Application

Introduction: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project. Methods: Figure 1 [see document] illustrates the IMM modeling system and scenario process. As illustrated, the IMM computational architecture is based on Probabilistic Risk Assessment techniques. Nineteen assumptions and limitations define the IMM application domain. Scenario definitions include crew medical attributes and mission specific details. The IMM forecasts probabilities of loss of crew life (LOCL), evacuation (EVAC), quality time lost during the mission, number of medical resources utilized and the number and type of medical events by combining scenario information with in-flight, analog, and terrestrial medical information stored in the iMED. In addition, the metrics provide the integrated information necessary to estimate optimized in-flight medical kit contents under constraints of mass and volume or acceptable level of mission risk. Results and Conclusions: Historically, IMM simulations support Science and Technology planning, Exploration mission planning, and ISS program operations by supplying simulation support, iMED data information, and subject matter expertise to Crew Health and Safety and the HRP. Upcoming release of IMM version 4.0 seeks to provide enhanced functionality to increase the quality of risk decisions made using the IMM through a more accurate representation of the real world system.

Myers, J.↗
NASA NTRS2015

Integrated Medical Model Overview

The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project.

Spae Adaptation Syndrome↗