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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydro-scaling of direct-drive cylindrical implosions at the OMEGA and the National Ignition Facility

Deceleration-phase Rayleigh–Taylor instability (RTI) growth during inertial confinement fusion capsule implosions significantly affects the performance as it mixes cold ablator material into the fuel. Precise measurements of such instability growth are essential for both validating the existing simulation codes and improving our predictive capability. RTI measurements on the inner surface of a spherical shell are limited and are often inferred indirectly at limited convergence. In contrast, cylindrical implosions allow for direct diagnostic access to the converging interface by imaging down the cylinder axis while retaining the effects of convergence. We have performed direct-drive cylindrical implosion experiments at both the OMEGA and the NIF laser facilities using scaled targets. RTI growth is demonstrated to be scale-invariant between the cylindrical targets at OMEGA and similar targets at the NIF, which are scaled up by a factor of three in the radial dimension. Single-mode (m = 0) instability growth factors of ~14 are measured at a convergence ratio (CR) ~ 2.5 with nearly identical mode growth at both scales. The measurements are in agreement with xRAGE radiation-hydrodynamics simulations. In addition, we have developed the Bayesian-inference-engine method to account for the variations in the target alignment, magnification, and the parallax effect in the measurement, allowing a more precise comparison between the experimental data and the simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

LANSCE Diagnostic Robot Localization

Los Alamos Neutron Science Center (LANSCE) operates a linear particle accelerator (LINAC) that is used for a number of scientific research projects. Due to the presence of harmful radiation, researchers are not allowed in the beam tunnel during operation. Since the beam tunnel is inaccessible, an autonomous mobile robot is to be developed and deployed in the tunnel, monitoring the accelerator during operation. The robot will present real time data for operators and scientists from sensors such as a video camera, thermal camera, microphones, and muon detectors; allowing for beam diagnostics previously unavailable. Localization is a fundamental step in autonomous navigation of mobile robots, answering the “where am I” question. For this project, an Extended Kalman Filter (EKF) algorithm is implemented as a positional estimator. The EKF relies on an odometric motion model to predict the robot’s position and LIDAR measurement data to update the robot’s position. The measurement model is based on v features extracted from the LIDAR point cluster using the Split-and-Merge algorithm, and the nearest neighbor algorithm associates the features to an a priori feature map of the beam tunnel. The predicted and measured positions are then joined using a weighted value by means of the Kalman gain. The effectiveness of this localization technique is demonstrated using the LabVIEW robotics simulator.

42 ENGINEERING↗
DOE OSTI2022

IER-517: Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK)

Nuclear criticality experiments are essential to the validation of nuclear data used in simulation software. The quality of nuclear data becomes paramount as simulation software becomes more relied upon for criticality safety studies and designs of nuclear systems. To improve the quality of nuclear data, experimenters can design critical experiments that are sensitive to isotope reaction pairs in materials of interest. The efforts conducted by the Organisation for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA) Working Party on Nuclear Criticality Safety (WPNCS) Subgroup 8: Preservation of Expert Knowledge and Judgement Applied to Criticality Benchmarks (SG8) to categorize benchmarks according to their usefulness for nuclear data validation have been of great importance. Based on the OECD studies benchmark experiments included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook are concisely used by nuclear data evaluators, criticality safety engineers and others to validate nuclear data and simulation results. A lack of benchmarks sensitive to molybdenum in the (ICSBEP), particularly in the intermediate range, was noted by Los Alamos National Laboratory (LANL), the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN), and Y-12 National Security Site prompting them to submit a joint integral experiment request to the Nuclear Criticality Safety Program (NCSP) in 2019. The request included both HEU and Plutonium systems in order to validate differential nuclear data focusing on the intermediate energy range but also includes thermal and fast configurations. This document represents the preliminary design work for a series of molybdenum integral experiments known as Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Numerical investigation of the flow inside the helical coil steam generator test section - 18589

A Helical Coil Steam Generator (HCSG) is one type of heat exchangers used for the purpose of increasing the efficiency of heat transfer with low pressure drop in recent design of high temperature reactors (HTRs). To investigate the fluid phenomena around the coil bundle of HCSG, the experimental facility had been designed and computational fluid dynamics (CFD) simulations had been conducted to compare the results of experimental ones. In this study, various types of turbulent models in the commercial CFD code (STAR-CCM+) were tested with various grid sizes on the target Reynolds number, Re{sub D} = 163,000, to enhance the validity of the simulation result. The computational domain used to run the CFD simulation had the same geometry of the experimental test section which had the half-coil shaped ribs on each curved channel wall. The working fluid properties employed in the simulation was scaled to the target Reynolds number at room temperature. The averaged static pressure drop induced by coil bundle inside the test section was obtained between the inlet and outlet of the test section. In addition, flow structures inside the flow channel were examined going through the velocity field distribution around the coil and the effect of vortical structures in the flow channel. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

On the physical and chemical details of alumina atomic layer deposition: A combined experimental and numerical approach

Alumina thin film is typically studied as a model atomic layer deposition (ALD) process due to its high dielectric constant, high thermal stability, and good adhesion on various wafer surfaces. Despite extensive applications of alumina ALD in microelectronics industries, details on the physical and chemical processes are not yet well understood. ALD experiments are not able to shed adequate light on the detailed information regarding the transient ALD process. Most of current numerical approaches lack detailed surface reaction mechanisms, and their results are not well correlated with experimental observations. In this paper, the authors present a combined experimental and numerical study on the details of flow and surface reactions in alumina ALD using trimethylaluminum and water as precursors. Results obtained from experiments and simulations are compared and correlated. By experiments, growth rate on five samples under different deposition conditions is characterized. The deposition rate from numerical simulation agrees well with the experimental results. Details of precursor distributions in a full cycle of ALD are studied numerically to bridge between experimental observations and simulations. The 3D transient numerical model adopts surface reaction kinetics and mechanisms based on atomic-level studies to investigate the surface deposition process. Surface deposition is shown as a strictly self-limited process in our numerical studies. ALD is a complex strong-coupled fluid, thermal and chemical process, which is not only heavily dependent on the chemical kinetics and surface conditions but also on the flow and material distributions.

42 ENGINEERING↗
DOE OSTI2023

IER 296 Experiment-Thermal Analysis and IRSN Response [Slides]

This set of slides summarizes progress, highlights, and issues related to the LANL design engineering effort for the IER 296 critical experiment. FEA simulation results are presented for the fuel elements on an insulated surface. Preliminary responses for the meeting agenda are documented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗
DOE OSTI2016

Characteristics Analysis of SGTR accidents under the Shutdown Conditions

The Steam Generator Tube Rupture (SGTR) accident is one of design basis accidents that could result in undesirable radiation release as it bypasses the containment. According to Ref. [1], SGTRs have been experienced in several nuclear power plants and Ulchin 4 of Korea is one of them. Basically, SGTR analysis assumes that it occurs at full power, the SGTR at Ulchin 4 in 2002, was in the shutdown condition. Therefore, the transient behavior was different from the cases in full power conditions and especially, the effectiveness of Emergency Operating Procedure (EOP) needs to be checked if it is also applicable to the shutdown conditions, because EOP is prepared for full power conditions. In this paper, we set up a MARS-KS code model for Ulchin 4 unit and simulated the SGTR accident for benchmarking the model to the actual plant behavior during the accident. And then, several case studies were done to investigate the consequence of SGTR and the effectiveness of the EOP, focusing on the amount of the primary to secondary discharge flow which was influenced by operator actions. At the end, we'll discuss about the EOP for the shutdown conditions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Telerobotic Control of Dexterous Dual-Arm Robots for D and D Operations - 18622

Robotic systems hold the potential to significantly reduce exposure of workers to hazardous environments such as in the deactivation and decommissioning (D and D) of nuclear facilities. Our goal is to enable an operator with minimal training to easily control a remote dual-arm robot to perform demolition tasks with hand tools. We propose a system that combines semi-autonomous coordination of the robot's arms with an intuitive operator interface based on virtual reality (VR) technology. A limb coordination system enables independent control of the robot arms, as well as coupled motion required to hold and manipulate rigid bodies such as reciprocating saws, angle grinders and crow bars. Using a VR head mounted display and stereo video from the robot for situational awareness and tracked VR hand controllers to command robot arm movement, an operator will be able to walk up to the control console, pick up the controllers, engage the manipulators, fly the grippers, grasp a tool with one or both robot arms and easily move them in unison to perform tasks. We present preliminary results using simulation and a physical dual-arm platform based on the Johns Hopkins University Applied Physics Laboratory's Modular Prosthetic Limb, an anthropomorphic device that provides hyper-dexterous human-like manipulation capabilities. Anticipated benefits of the robotic system for D and D operations include improved situational awareness, increased mission complexity, and reduced operator training time, workload, and task execution times. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Self-similar Reynolds-averaged mechanical–scalar turbulence models for Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing in the small Atwood number limit

Analytical self-similar solutions to two-, three-, and four-equation Reynolds-averaged mechanical–scalar turbulence models describing incompressible turbulent Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing in planar geometry are derived in the small Atwood number (Boussinesq) limit. The models are based on the turbulent kinetic energy K and its dissipation rate ε, together with the scalar (heavy-fluid mass fraction) variance S and its dissipation rate Χ modeled either differentially or algebraically. The models allow for a simultaneous description of mechanical and scalar mixing, i.e., mixing layer growth and molecular mixing, respectively. Mixing layer growth parameters and other physical observables relevant to each instability are obtained explicitly as functions of the model coefficients. The turbulent fields are also expressed in terms of the model coefficients, with their temporal power-law scalings obtained by requiring that the self-similar equations are explicitly time-independent. The model calibration methodology is described and discussed. Expressions for a subset of the various physical observables are used to calibrate each of the two-, three-, and four-equation models, such that the self-similar solutions are consistent with experimental and numerical simulation data corresponding to these values of the observables and to specific canonical Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz turbulent flows. A calibrated four-equation model is then used to reconstruct the mean and turbulent fields, and late-time turbulent equation budgets for each instability-induced flow across the mixing layer. The reference solutions derived here can provide systematic calibrations and better understanding of mechanical–scalar turbulence models and their predictions for instability-induced turbulent mixing in the very large Reynolds number limit.

42 ENGINEERING↗
DOE OSTI2016

Failure Diagnosis for the Holdup Tank System via ISFA

This paper discusses the use of the integrated system failure analysis (ISFA) technique for fault diagnosis for the holdup tank system. ISFA is a simulation-based, qualitative and integrated approach used to study fault propagation in systems containing both hardware and software subsystems. The holdup tank system consists of a tank containing a fluid whose level is controlled by an inlet valve and an outlet valve. We introduce the component and functional models of the system, quantify the main parameters and simulate possible failure-propagation paths based on the fault propagation approach, ISFA. The results show that most component failures in the holdup tank system can be identified clearly and that ISFA is viable as a technique for fault diagnosis. Since ISFA is a qualitative technique that can be used in the very early stages of system design, this case study provides indications that it can be used early to study design aspects that relate to robustness and fault tolerance. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗
DOE OSTI2017

Computation of Air Discharge into a Water Pool by Using Volume-of-Fluid Method

Suppression tanks, in-containment refueling water storage tanks (IRWSTs) and filtered containment venting systems (FCVSs) of nuclear power plants use water pools to accommodate high-pressure and high-temperature discharge of non-condensable gases and/or steam. Dynamic behavior of gas bubbles inside a water pool determines pressure and temperature loading to the system and thus we need validated method for applications. The underlying physics relevant to these problems is still a difficult issue due to the complicated nature of gas- liquid interfacial transfers of mass, momentum, and energy in a two-phase flow. Therefore, notwithstanding many studies performed over the past two or three decades, two-fluid theory is still a formidable task and direct numerical simulation (DNS) needs huge computing cost. Pellegrini et al. analyzed steam condensation and chugging in the water pool of the PPOOLEX STB-24 test by using STAR-CCM+ code implemented with two-phase interface model based on the Rayleigh-Taylor instability theory (RTI) which triggers steam depressurization. For the solution of the fine interface, they used Eulerian-Eulerian model for the fluid domain since the volume-of-fluid (VOF) model requires larger mesh points. The RTI resulted in complete steam condensation consistent with the experiment. The fluid tank was open to the atmosphere. They reported the volume fraction distributions in the pool, not the pool temperature or pressure history. For non-condensing gas discharges, however, the VOF is still a good alternative to the Eulerian two-fluid or the DNS approaches. The spatial distribution of each phase is defined in terms of volume fractions and the cell physical properties are obtained from linear combinations of those of constituent phases weighted by each volume fraction. Therefore, conditions where thermal and phase change effects become important are less likely to be simulated realistically. The VOF model is suited for the simulation of flows where each phase constitutes a large structure with a relatively small total contact area between phases. Present work is also interested in this VOF method for application to air discharge into a water pool which occurs in the early operating stages of the said facilities. Our purpose is to validate the VOF method against an existing air discharge experiment of PPOOLEX by using a commercial CFD code, STAR-CCM+ version 10.04, in terms of macroscopic flow properties. Effect of turbulence is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING↗