SEARCH · Search NASA

Results for “Human in the Loop”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

All sources NASA NTRS DOE OSTI

NASA NTRS2010

Managing Demand and Capacity Using Multi-Sector Planning and Flexible Airspace: Human-in-the-Loop Evaluation of NextGen

When demand for an airspace sector exceeds capacity, the balance can be re-established by reducing the demand, increasing the capacity, or both. The Multi-Sector Planner (MSP) concept has been proposed to better manage traffic demand by modifying trajectories across multiple sectors. A complementary approach to MSP, called Flexible Airspace Management (FAM), reconfigures the airspace such that capacity can be reallocated dynamically to balance the traffic demand across multiple sectors, resulting in fewer traffic management initiatives. The two concepts have been evaluated with a series of human-in-the-loop simulations at the Airspace Operations Laboratory to examine and refine the roles of the human operators in these concepts, as well as their tools and procedural requirements. So far MSP and FAM functions have been evaluated individually but the integration of the two functions is desirable since there are significant overlaps in their goals, geographic/temporal scope of the problem space, and the implementation timeframe. Ongoing research is planned to refine the humans roles in the integrated concept.

Lee, Paul U.↗

DOE OSTI2023

A General Framework for Human-in-the-Loop Cognitive Digital Twins

Modelling and analysis of systems that are equipped with sensors and connected to the Internet are becoming more automated and less human-dependent. However, bringing expert knowledge into the loop along with data obtained from Internet of Thing (IoT) devices minimizes the risk of making poor and unexplainable decisions and helps to assess the impact of different strategies before applying them in reality. While Digital Twins are more of a data-driven simulation of the physical system, Cognitive Digital Twins bring the human dimension into the modelling and simulation. In this paper, we aim to emphasize the crucial role of explainability and the underlying rationale behind automated or interactive decision-making processes. Furthermore, we propose an initial framework that delineates the specific points within the feedback loop of a cognitive digital twin where human involvement can be incorporated.

Niloofar, Parisa↗

DOE OSTI2024

Human-in-the-Loop: The Future of Machine Learning in Automated Electron Microscopy

Machine learning (ML) methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-acquisition. The introduction of the application programming interfaces (APIs) by major instrument manufacturers now allows the deployment of ML workflows in microscopes, not only for data analytics but also for real-time decision-making and feedback for microscope operation. However, the number of use cases for real-time ML remains remarkably small. Furthermore, we discuss some considerations in designing ML-based active experiments and pose that the likely strategy for the next several years will be human-in-the-loop automated experiments (hAE). In this paradigm, the ML learning agent directly controls beam position and image and spectroscopy acquisition functions, and a human operator monitors experiment progression in real and feature space of the system and tunes the policies of the ML agent to steer the experiment toward specific objectives.

47 OTHER INSTRUMENTATION↗

NASA NTRS1993

Human-in-the-loop evaluation of RMS Active Damping Augmentation

Active Damping Augmentation is the insertion of Controls-Structures Integration Technology to benefit the on-orbit performance of the Space Shuttle Remote Manipulator System. The goal is to reduce the vibration decay time of the Remote Manipulator System following normal payload maneuvers and operations. Simulation of Active Damping Augmentation was conducted in the realtime human-in-the-loop Systems Engineering Simulator at the NASA Johnson Space Center. The objective of this study was to obtain a qualitative measure of operational performance improvement from astronaut operators and to obtain supporting quantitative performance data. Sensing of vibratory motions was simulated using a three-axis accelerometer mounted at the end of the lower boom of the Remote Manipulator System. The sensed motions were used in a feedback control law to generate commands to the joint servo mechanisms which reduced the unwanted oscillations. Active damping of the Remote Manipulator System with an attached 3990 lb. payload was successfully demonstrated. Six astronaut operators examined the performance of an Active Damping Augmentation control law following single-joint and coordinated six-joint translational and rotational maneuvers. Active Damping Augmentation disturbance rejection of Orbiter thruster firings was also evaluated. Significant reductions in the dynamic response of the 3990 lb. payload were observed. Astronaut operators recommended investigation of Active Damping Augmentation benefits to heavier payloads where oscillations are a bigger problem (e.g. Space Station Freedom assembly operators).

Demeo, Martha E.↗

NASA NTRSDate not supplied

Teal Cycle Ergometer Vibration Isolation and Stabilization System Human-in-the-Loop Ground Evaluation for Long-Duration Spaceflight

Purpose: To counter the deleterious effects of weightlessness on the cardiopulmonary system, astronauts living on the International Space Station exercise on a variety of countermeasure equipment including the Cycle Ergometer Vibration Isolation and Stabilization System (CEVIS). Operational since 2001, the onboard CEVIS will be replaced by a new model, known as Teal CEVIS (TC). As a part of ground evaluation, TC hardware underwent human-in-the-loop (HITL) testing to verify the TC hardware produces workloads that elicit physiologic responses comparable to a laboratory cycle ergometer (LAB). Methods: Seven subjects (5 M/2 F) performed submaximal cycle ergometer testing with indirect calorimetry measures on TC and LAB on separate test days. Testing consisted of graded 30 watt increases in workload until subjects reached 85% of age-predicted max heart rate (HR). Exercise outcomes included rate of oxygen uptake (VO2; liters/min), rate of energy expenditure (REE; kcal/min), and HR (beats/min). Linear mixed models (LMM) were fitted to compare VO2, REE, and HR responses between devices across power outputs with fixed effects for power (P) and device (D) and with random effects for subject. LMM effect coefficients (β), std errors (SE), pseudo-partial R2 of effects (pR2), and model likelihood ratio statistics (χ2, Pr(> chisq); α<.05) are provided. Results: LMM main effects for P and D were observed for VO2 (βp=.0107, SE = .0002, pR2=0.97; βd = -0.075, SE = 0.019, pR2=0.14; χ2(1)= 13.57, p<.001), such that VO2 was higher across stages on TC. Main effects of P and D were observed for REE (βp= .0586, SE = 0.001, pR2= 0.97; βd = -0.33208, SE = 0.099, pR2= 0.056; χ2(1)=10.481, p < .01), such that REE was higher across power outputs on TC. A P x D interaction was observed for HR, along with main effects for P and D (βp x d =-0.048, SE = 0.02, pR2=0.048; βp= 0.42, SE = 0.016, pR2=0.87; χ2(1) = 5.398, p = 0.02), such that higher workloads elicited a greater difference in HR between devices. Conclusions: HITL results show, TC elicits greater physiologic responses across power outputs compared to LAB. However, pR2 for device effects show small differences between devices. Therefore, TC can be expected to provide appropriate physiological stimulus across workloads and be considered a reliable tool to mitigate the effects of weightlessness.

Cycle Ergometer Vibration and Isolation System↗

NASA NTRS2016

Space Suit Portable Life Support System (PLSS) 2.0 Human-in-the-Loop (HITL) Testing

The space suit Portable Life Support System (PLSS) 2.0 represents the second integrated prototype developed and tested to mature a design that uses advanced technologies to reduce consumables, improve robustness, and provide additional capabilities over the current state of the art. PLSS 2.0 was developed in 2012, with extensive functional evaluations and system performance testing through mid-2014. In late 2014, PLSS 2.0 was integrated with the Mark III space suit in an ambient laboratory environment to facilitate manned testing, designated PLSS 2.0 Human-in-the-Loop (HITL) testing, in which the PLSS prototype performed the primary life support functions, including suit pressure regulation, ventilation, carbon dioxide control, and cooling of the test subject and PLSS avionics. The intent of this testing was to obtain subjective test subject feedback regarding qualitative aspects of PLSS 2.0 performance such as thermal comfort, sounds, smells, and suit pressure fluctuations due to the cycling carbon dioxide removal system, as well as to collect PLSS performance data over a range of human metabolic rates from 500-3000 Btu/hr. Between October 27 and December 18, 2014, nineteen two-hour simulated EVA test points were conducted in which suited test subjects walked on a treadmill to achieve a target metabolic rate. Six test subjects simulated nominal and emergency EVA conditions with varied test parameters including metabolic rate profile, carbon dioxide removal control mode, cooling water temperature, and Liquid Cooling and Ventilation Garment (state of the art or prototype). The nineteen test points achieved more than 60 hours of test time, with 36 hours accounting for simulated EVA time. The PLSS 2.0 test article performed nominally throughout the test series, confirming design intentions for the advanced PLSS. Test subjects' subjective feedback provided valuable insight into thermal comfort and perceptions of suit pressure fluctuations that will influence future advanced PLSS design and testing strategies.

Watts, Carly↗

NASA NTRS2016

Space Suit Portable Life Support System (PLSS) 2.0 Human-in-the-Loop (HITL) Testing

Watts, Carly↗

NASA NTRSDate not supplied

Human-in-the-Loop Flight Simulation Experiment on Unmanned Aircraft Terminal Operations

A Detect and Avoid (DAA) System is a suite of sensors, tracker, and alerting and guidance algorithms that assist a remote pilot of an Unmanned Aircraft System in maintaining separation from airborne traffic by complying with current ‘see and avoid’ requirements. To date, work has focused on operations transiting to and from Class A or special use airspace. Current efforts are defining DAA system requirements for operations in and around terminal airspace. As a contribution to the current efforts, this paper presents results from a Human-in-the-Loop experiment comparing methods of changing from the transit-specific alerting and guidance criteria to the reduced terminal-specific alerting and guidance criteria.

Devin Patrick Jack↗

DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗

DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Bone Conduction Headphone Research and Human-in-the-Loop Test Results

The new space suit being developed for exploration EVAs on the surface of the Moon and in microgravity environments is called xEMU. A government reference model had been developed and had undergone testing. This suit contains new upgrades from the current EMU on ISS, such as integrated speakers and microphones, eliminating the need for astronauts to wear a Communications Carrier Assembly (CCA) on their head during spacewalks. However, upon testing, it was noticed that this feature causes acoustic coupling, that results in communications echo and feedback. A proposed solution to this issue is to have the astronaut wear a bone conduction headset for audio capabilities while on EVA to receive incoming voice communications from Mission Control and other EVA or IVA crew members. This would eliminate the acoustic coupling and echo effect while being more ergonomically sound than the current CCA and leave the ear open to suit ambient sound for situational awareness. A human-in-the-loop evaluation was performed, comparing five commercially available bone conduction headsets, to evaluate comfort, fit, and adjustability for long-duration wear. Five engineering test subjects with different head sizes were utilized to wear the headsets for six hours and provide succinct feedback and score the headsets on a variety of factors, to help determine which of the headsets performed the best and could advance to future bone conduction audio testing. Three of the headsets were well-received among the diverse group of subjects, and at least one of these will advance to further testing to be considered for future use under the xEMU helmet for exploration EVAs. Rating results and evaluation methods for this bone conduction headset evaluation will be presented.

Bridget M Cavanaugh↗

NASA NTRS2010

Preliminary Human-in-the-Loop Assessment of Procedures for Very-Closely-Spaced Parallel Runways

Demand in the future air transportation system concept is expected to double or triple by 2025 [1]. Increasing airport arrival rates will help meet the growing demand that could be met with additional runways but the expansion airports is met with environmental challenges for the surrounding communities when using current standards and procedures. Therefore, changes to airport operations can improve airport capacity without adding runways. Building additional runways between current ones, or moving them closer, is a potential solution to meeting the increasing demand, as addressed by the Terminal Area Capacity Enhancing Concept (TACEC). TACEC requires robust technologies and procedures that need to be tested such that operations are not compromised under instrument meteorological conditions. The reduction of runway spacing for independent simultaneous operations dramatically exacerbates the criticality of wake vortex incursion and the calculation of a safe and proper breakout maneuver. The study presented here developed guidelines for such operations by performing a real-time, human-in-the-loop simulation using precision navigation, autopilot-flown approaches, with the pilot monitoring aircraft spacing and the wake vortex safe zone during the approach.

Verma, Savita↗

NASA NTRS2012

Comparisons of a Constrained Least Squares Model Versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a "reddening" of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object's suspected material component will be discussed herein.

Rapp, Jason↗

NASA NTRS2013

Comparisons of a Constrained Least Squares Model versus Human-in-the-Loop for Spectral Unmixing to Determine Material Type of GEO Debris

Spectral reflectance data through the visible regime was collected at Las Campanas Observatory in Chile using an imaging spectrograph on one of the twin 6.5-m Magellan telescopes. The data were obtained on 1-2 May 2012 on the 'Landon Clay' telescope with the LDSS3 (Low Dispersion Survey Spectrograph 3). Five pieces of Geosynchronous Orbit (GEO) or near-GEO debris were identified and observed with an exposure time of 30 seconds on average. In addition, laboratory spectral reflectance data was collected using an Analytical Spectral Device (ASD) field spectrometer at California Polytechnic State University (Cal Poly) in San Luis Obispo on several typical common spacecraft materials including solar cells, circuit boards, various Kapton materials used for multi-layer insulation, and various paints. The remotely collected data and the laboratory-acquired data were then incorporated in a newly developed model that uses a constrained least squares method to unmix the spectrum in specific material components. The results of this model are compared to the previous method of a human-in-the-loop (considered here the traditional method) that identifies possible material components by varying the materials and percentages until a spectral match is obtained. The traditional model was found to match the remotely collected spectral data after it had been divided by the continuum to remove the space weathering effects, or a reddening of the materials. The constrained least-squares model also used the de-reddened spectra as inputs and the results were consistent with those obtained through the traditional method. For comparison, a first-order examination of including reddening effects into the constrained least-squares model will be explored and comparisons to the remotely collected data will be examined. The identification of each object s suspected material component will be discussed herein.

Abercromby, Kira J.↗

NASA NTRS2016

A Human-in-the Loop Evaluation of a Coordinated Arrival Departure Scheduling Operations for Managing Departure Delays at LaGuardia Airport

LaGuardia (LGA) departure delay was identified by the stakeholders and subject matter experts as a significant bottleneck in the New York metropolitan area. Departure delay at LGA is primarily due to dependency between LGA's arrival and departure runways: LGA departures cannot begin takeoff until arrivals have cleared the runway intersection. If one-in one-out operations are not maintained and a significant arrival-to-departure imbalance occurs, the departure backup can persist through the rest of the day. At NASA Ames Research Center, a solution called "Departure-sensitive Arrival Spacing" (DSAS) was developed to maximize the departure throughput without creating significant delays in the arrival traffic. The concept leverages a Terminal Sequencing and Spacing (TSS) operations that create and manage the arrival schedule to the runway threshold and added an interface enhancement to the traffic manager's timeline to provide the ability to manually adjust inter-arrival spacing to build precise gaps for multiple departures between arrivals. A more complete solution would include a TSS algorithm enhancement that could automatically build these multi-departure gaps. With this set of capabilities, inter-arrival spacing could be controlled for optimal departure throughput. The concept was prototyped in a human-in-the- loop (HITL) simulation environment so that operational requirements such as coordination procedures, timing and magnitude of TSS schedule adjustments, and display features for Tower, TRACON and Traffic Management Unit could be determined. A HITL simulation was conducted in August 2014 to evaluate the concept in terms of feasibility, controller workload impact, and potential benefits. Three conditions were tested, namely a Baseline condition without scheduling, TSS condition that schedules the arrivals to the runway threshold, and TSS+DSAS condition that adjusts the arrival schedule to maximize the departure throughput. The results showed that during high arrival demand period, departure throughput could be incrementally increased under TSS and TSS+DSAS conditions without compromising the arrival throughput. The concept, operational procedures, and summary results were originally published in ATM20151 but detailed results were omitted. This paper expands on the earlier paper to provide the detailed results on throughput, conformance, safety, flight time/distance, etc. that provide extra insights into the feasibility and the potential benefits on the concept.

trajectory-based operations↗

DOE OSTI2025

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗

NASA NTRS2018

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-In-The-Loop Simulation

The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) poses a variety of technical challenges to UAS developers and aviation regulators. In response to growing demand for access to civil airspace in the United States, the Federal Aviation Administration (FAA) has produced a roadmap identifying key areas requiring further research and development. One such technical challenge is the development of a "detect and avoid" system (DAA) capable of providing a means of compliance with the "see and avoid" requirement in manned aviation. The purpose of the DAA system is to support the pilot, situated at a ground control station (GCS), in maintaining "DAA well clear" of nearby aircraft through the use of GCS displays and alerts. In addition to its primary function of aiding the pilot in maintaining DAA well clear, the DAA system must also safely interoperate with existing NAS systems and operations, such as the airspace management procedures of air traffic controllers (ATC) and Collision Avoidance (CA) systems currently in use by manned aircraft, namely the Traffic Alert and Collision Avoidance System (TCAS II). It is anticipated that many UAS architectures will integrate both a DAA system and a TCAS II. It is therefore necessary to explicitly study the integration of DAA and TCAS II alerting structures and maneuver guidance formats to ensure that pilots understand the appropriate type and urgency of their response to the various alerts. This paper presents a concept of interoperability for the two systems. The concept was developed with the goal of avoiding any negative impact on the performance level of TCAS II while retaining a DAA system that still effectively enables pilots to maintain DAA well clear. The interoperability concept described in the paper focuses primarily on facilitating the transition from a late-stage DAA encounter (where a loss of DAA well clear is imminent) to a TCAS II Corrective Resolution Advisory (RA), which requires pilot compliance within five seconds of its issuance. The interoperability concept was presented to 10 participants (6 active UAS pilots and 4 active commercial pilots) in a medium-fidelity, human-in-the-loop simulation designed to stress different aspects of the DAA and TCAS II systems. Pilots' ability to maintain separation, their rate of compliance and response times using the interoperability concept are reported. Results indicated that pilots exhibited comprehension of, and appropriate prioritization within, the DAA-TCAS II combined alert structure. Pilots demonstrated a high rate of compliance with TCAS II RAs and were also seen to respond to corrective RAs within the five second requirement established for manned aircraft. The DAA system presented under test was also shown to be effective in supporting pilots' ability to maintain DAA well clear in the overwhelming majority of cases in which pilots had sufficient time to respond.

Rorie, R. Conrad↗

NASA NTRS2004

NASA Processes and Requirements for Conducting Human-in-the-Loop Closed Chamber Tests

NASA has specific processes and requirements that must be followed for tests involving human subjects to be conducted in a safe and effective manner. There are five distinct phases of test operations. Phase one, the test request phase, consists of those activities related to initiating, processing, reviewing, and evaluating the test request. Phase two, the test preparation phase consists of those activities related to planning, coordinating, documenting, and building up the test. Phase three, the test readiness phase consists of those activities related to verifying and reviewing the planned test operations. Phase four, the test activity phase, consists of all pretest operations, functional checkouts, emergency drills, and test operations. Phase five, the post test activity phase, consists of those activities performed once the test is completed, including briefings, documentation of anomalies, data reduction and archiving, and reporting. Project management processes must be followed for facility modifications and major test buildup, which include six phases: initiation and assessment, requirements evaluation, preliminary design, detailed design, use readiness review (URR) and acceptance. Compliance with requirements for safety and quality assurance are documented throughout the test buildup and test operation processes. Tests involving human subjects must be reviewed by the applicable Institutional Review Board (IRB).

Barta, Daniel J.↗