Engineering topics

Goodenow, Debra

Publications and source records attributed to Goodenow, Debra.

5 records

NASA NTRS2020

MEDPRAT-SEL: Medical Resource Set Selector Searching High-Dimensionality Space

NASA Human Research Program's (HRP) next generation risk model closes the loop on medical risk and resource evaluation, providing researchers with a tool to assess and choose capabilities scientifically. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) simulator (SIM) evaluates resources in terms of medical benefit, such as reduced crew quality time lost (QTL), vs. cost, in mass or volume. The MEDPRAT resource set selector (SEL) searches the space of resource benefits v. cost, closing a feedback loop around the simulator, thus selecting resource sets with best benefit for cost. We discuss the design and results of the resource set selector. NASA HRP's emphasis on scientific assessment of risk, PRA, has led to the Cross-cutting Computational Modeling Project (CCMP).

Leinweber, Lawrence↗

NASA NTRS2018

Validation of the Nasa Integrated Medical Model: a Space Flight Medical Risk Prediction Tool

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.

medical equipment↗

NASA NTRS2016

Flight Analysis of an Autonomously Navigated Experimental Lander for High Altitude Recovery

First steps have been taken to qualify a family of parafoil systems capable of increasing the survivability and reusability of high-altitude balloon payloads. The research is motivated by the common risk facing balloon payloads where expensive flight hardware can often land in inaccessible areas that make them difficult or impossible to recover. The Autonomously Navigated Experimental Lander (ANGEL) flight test introduced a commercial Guided Parachute Aerial Delivery System (GPADS) to a previously untested environment at 108,000ft MSL to determine its high-altitude survivability and capabilities. Following release, ANGEL descended under a drogue until approximately 25,000ft, at which point the drogue was jettisoned and the main parachute was deployed, commencing navigation. Multiple data acquisition platforms were used to characterize the return-to-point technology performance and help determine its suitability for returning future scientific payloads ranging from 180 to 10,000lbs to safer and more convenient landing locations. This report describes the test vehicle design, and summarizes the captured sensor data. Various post-flight analyses are used to quantify the system's performance, gondola load data, and serve as a reference point for subsequent missions.

Parafoil↗

NASA NTRS2016

Flight Analysis of an Autonomously Navigated Experimental Lander

First steps have been taken to qualify a family of parafoil systems capable of increasing the survivability and reusability of high-altitude balloon payloads. The research is motivated by the common risk facing balloon payloads where expensive flight hardware can often land in inaccessible areas that make them difficult or impossible to recover. The Autonomously Navigated Experimental Lander (ANGEL) flight test introduced a commercial Guided Parachute Aerial Delivery System (GPADS) to a previously untested environment at 108,000 feet Mean Sea Level (MSL) to determine its high-altitude survivability and capabilities. Following release, ANGEL descended under a drogue until approximately 25,000 feet, at which point the drogue was jettisoned and the main parachute was deployed, commencing navigation. Multiple data acquisition platforms were used to characterize the return-to-point technology performance and help determine its suitability for returning future scientific payloads ranging from 180 to 10,000 pounds to safer and more convenient landing locations. This report describes the test vehicle design, and summarizes the captured sensor data. Various post-flight analyses are used to quantify the systems performance, gondola load data, and serve as a reference point for subsequent missions.

Parafoil↗

NASA NTRS2004

Model of a Piezoelectric Transducer

It's difficult to control liquid and gas in propellant tanks in zero gravity. A possible a design would utilize acoustic liquid manipulation (ALM) technology which uses ultrasonic beams conducted through a liquid and solid media, to push gas bubbles in the liquid to desirable locations. We can propel and control the bubble with acoustic radiation pressure by aiming the acoustic waves on the bubble s surface. This allows us to design a so called smart tank in which the ALM devices transfer the gas to the outer wall of the tank and isolating the liquid in the center. Because the heat transfer rate of a gas is lower of that of the liquid it would substantially decrease boil off and provide of for a longer storage life. The ALM beam is composed of little wavelets which are individual waves that constructively interfere with each other to produce a single, combined acoustic wave front. This is accomplished by using a set of synchronized ultrasound transducers arranged in an array. A slight phase offset of these elements allows us to focus and steer the beam. The device that we are using to produce the acoustic beam is called the piezoelectric transducer. This device converts electrical energy to mechanical energy, which appears in the form of acoustic energy. Therefore the behavior of the device is dependent on both the mechanical characteristics, such as its density, cross-sectional area, and its electrical characteristics, such as, electric flux permittivity and coupling factor. These devices can also be set up in a number of modes which are determined by the way the piezoelectric device is arranged, and the shape of the transducer. For this application we are using the longitudinal or thickness mode for our operation. The transducer also vibrates in the lateral mode, and one of the goals of my project is to decrease the amount of energy lost to the lateral mode. To model the behavior of the transducers I will be using Pspice, electric circuit modeling tool, to determine the transducer's electrical characteristics at the frequency of interest. This will also help me determine the characteristics of an impedance matching network to operate the transducer at its optimum efficiency. For this I will use ABMs (analog behavioral modeling) to model dependent current and voltage sources that represent the transducer. I have also been working on the Labview control software for the phased array used to control the bubbles, and will begin testing on that before the end of my internship.

Goodenow, Debra↗