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Dinzl, Derek John

Publications and source records attributed to Dinzl, Derek John.

14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Nuclear Risk Assessment 2019 Update for the Mars 2020 Mission Environmental Impact Statement

In the summer of 2020, the National Aeronautics and Space Administration (NASA) plans to launch a spacecraft as part of the Mars 2020 mission. The rover on the proposed spacecraft will use a Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) to provide continuous electrical and thermal power for the mission. The MMRTG uses radioactive plutonium dioxide. NASA is preparing a Supplemental Environmental Impact Statement (SEIS) for the mission in accordance with the National Environmental Policy Act. This Nuclear Risk Assessment addresses the responses of the MMRTG option to potential accident and abort conditions during the launch opportunity for the Mars 2020 mission and the associated consequences. This information provides the technical basis for the radiological risks discussed in the SEIS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Interpolation of V-Gamma Map Failure Data for Use with LAPS

This document outlines the approach used for interpolation of a dataset provided by the Jet Propulsion Laboratory (JPL) which contains failure predictions of the Mars 2020 entry vehicle (EV). JPL used Navier-Stokes simulations to predict the failure altitude of the EV, along with a corresponding velocity and flight path angle at failure. These simulations were executed for several initial trajectory points in the entry envelope (the V-Gamma map).

42 ENGINEERING↗
DOE OSTI2019

Estimation of inflow uncertainties in laminar hypersonic double-cone experiments

We propose herein a probabilistic framework for assessing the consistency of an experimental dataset, i.e., whether the stated experimental conditions are consistent with the measurements provided. In case the dataset is inconsistent, our framework allows one to hypothesize and test sources of inconsistencies. This is crucial in model validation efforts. The framework relies on Bayesian inference to estimate experimental settings deemed uncertain, from measurements deemed accurate. The quality of the inferred variables is gauged by its ability to reproduce held-out experimental measurements. We test the correctness of the framework on three double-cone experiments conducted in the CUBRC Inc.'s LENS-I shock tunnel, which have also been numerically simulated successfully. Thereafter, we use the framework to investigate two double-cone experiments (executed in the LENS-XX shock tunnel) which have encountered difficulties when used in model validation exercises. We detect an inconsistency with one of the LENS-XX experiments. In addition, we hypothesize two causes for our inability to simulate LEXS-XX experiments accurately and test them using our framework. We find that there is no single cause that explains all the discrepancies between model predictions and experimental data, but different causes explain different discrepancies, to larger or smaller extent. We end by proposing that uncertainty quantification methods be used more widely to understand experiments and characterize facilities, and we cite three different methods to do so, the third of which we present in this paper.

Thermophysics↗