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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Analysis of Skeletal Muscle Metrics as Predictors of Functional Task Performance

PURPOSE: The ability to predict task performance using physiological performance metrics is vital to ensure that astronauts can execute their jobs safely and effectively. This investigation used a weighted suit to evaluate task performance at various ratios of strength, power, and endurance to body weight. METHODS: Twenty subjects completed muscle performance tests and functional tasks representative of those that would be required of astronauts during planetary exploration (see table for specific tests/tasks). Subjects performed functional tasks while wearing a weighted suit with additional loads ranging from 0-120% of initial body weight. Performance metrics were time to completion for all tasks except hatch opening, which consisted of total work. Task performance metrics were plotted against muscle metrics normalized to "body weight" (subject weight + external load; BW) for each trial. Fractional polynomial regression was used to model the relationship between muscle and task performance. CONCLUSION: LPMIF/BW is the best predictor of performance for predominantly lower-body tasks that are ambulatory and of short duration. LPMIF/BW is a very practical predictor of occupational task performance as it is quick and relatively safe to perform. Accordingly, bench press work best predicts hatch-opening work performance.

Ryder, Jeffrey W.↗
NASA NTRS2010

Normalized Point Source Sensitivity for Off-Axis Optical Performance Evaluation of the Thirty Meter Telescope

The Normalized Point Source Sensitivity (PSSN) has previously been defined and analyzed as an On-Axis seeing-limited telescope performance metric. In this paper, we expand the scope of the PSSN definition to include Off-Axis field of view (FoV) points and apply this generalized metric for performance evaluation of the Thirty Meter Telescope (TMT). We first propose various possible choices for the PSSN definition and select one as our baseline. We show that our baseline metric has useful properties including the multiplicative feature even when considering Off-Axis FoV points, which has proven to be useful for optimizing the telescope error budget. Various TMT optical errors are considered for the performance evaluation including segment alignment and phasing, segment surface figures, temperature, and gravity, whose On-Axis PSSN values have previously been published by our group.

optical performance metric↗
NASA NTRS1991

Stochastic robustness

To carry out stochastic robustness analysis, an expected probability distribution is assigned to each uncertain parameter in the system. The Monte Carlo analysis proceeds by repeatedly assigning shaped random values to each plant parameter, evaluating the stability of performance metric, and performing the binary classification (stable/unstable, etc.). If the system is stable, the state response to a unit disturbance impulse can be propagated to establish whether the response would violate settling time envelopes and whether peak actuator use would violate predetermined maximums. The final estimates of the probability of each form of unacceptable behavior are found by dividing the number of cases in which the overall system had that form of unacceptability by the number of cases run. Stability robustness can be portrayed graphically using the stochastic root locus and by using histograms of parameter values found in the unacceptable cases.

Marrison, C.↗
NASA NTRS1997

Application of Domain Knowledge to Software Quality Assurance

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Wild, Christian W.↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
NASA NTRS2006

Truss Performance and Packaging Metrics

In the present paper a set of performance metrics are derived from first principals to assess the efficiency of competing space truss structural concepts in terms of mass, stiffness, and strength, for designs that are constrained by packaging. The use of these performance metrics provides unique insight into the primary drivers for lowering structural mass and packaging volume as well as enabling quantitative concept performance evaluation and comparison. To demonstrate the use of these performance metrics, data for existing structural concepts are plotted and discussed. Structural performance data is presented for various mechanical deployable concepts, for erectable structures, and for rigidizable structures.

Mikulas, Martin M.↗
NASA NTRS1997

Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori error analysis capability has been developed which provides probabilistic error estimates on the true performance for a design randomly selected near the surrogate-predicted optimal design.

Patera, Anthony T.↗
NASA NTRS1993

ACSYNT inner loop flight control design study

The NASA Ames Research Center developed the Aircraft Synthesis (ACSYNT) computer program to synthesize conceptual future aircraft designs and to evaluate critical performance metrics early in the design process before significant resources are committed and cost decisions made. ACSYNT uses steady-state performance metrics, such as aircraft range, payload, and fuel consumption, and static performance metrics, such as the control authority required for the takeoff rotation and for landing with an engine out, to evaluate conceptual aircraft designs. It can also optimize designs with respect to selected criteria and constraints. Many modern aircraft have stability provided by the flight control system rather than by the airframe. This may allow the aircraft designer to increase combat agility, or decrease trim drag, for increased range and payload. This strategy requires concurrent design of the airframe and the flight control system, making trade-offs of performance and dynamics during the earliest stages of design. ACSYNT presently lacks means to implement flight control system designs but research is being done to add methods for predicting rotational degrees of freedom and control effector performance. A software module to compute and analyze the dynamics of the aircraft and to compute feedback gains and analyze closed loop dynamics is required. The data gained from these analyses can then be fed back to the aircraft design process so that the effects of the flight control system and the airframe on aircraft performance can be included as design metrics. This report presents results of a feasibility study and the initial design work to add an inner loop flight control system (ILFCS) design capability to the stability and control module in ACSYNT. The overall objective is to provide a capability for concurrent design of the aircraft and its flight control system, and enable concept designers to improve performance by exploiting the interrelationships between aircraft and flight control system design parameters.

Bortins, Richard↗
NASA NTRSDate not supplied

Risk Characterization Research for Artemis II: Human Factors and Behavioral Performance

BACKGROUND Artemis II will be the first time NASA astronauts go beyond low-Earth orbit (LEO) since the Apollo era, and the first astronauts heading into space in the Orion vehicle. As such, it provides a critical opportunity to refine our understanding of the likelihood and consequences associated with the Behavioral Medicine (BMed), Team, Human System Integration Architecture (HSIA), and Sleep Risks, and prepare for future Moon and Mars missions. However, Artemis II research efforts are uniquely shaped by in-mission data collection constraints. There is currently no in-mission crew time available to complete measures. In-mission data will need to be collected unobtrusively from available data streams (e.g., audiovisual, existing records such as schedules, and actigraphy). Accordingly, the overarching goal of our research is to utilize Artemis II data to further define the likelihood and consequences of these risks, and to create an unobtrusive research infrastructure that can be expanded to include future Artemis missions. This goal spans four aims across three research phases: (1) identify and operationally define key performances metrics and constructs across the four aforementioned risks, (2) develop an unobtrusive methodology and coding scheme for in-mission data collection, (3) characterize performance decrements due to Bmed, Team, HSIA, and Sleep Risks, and (4) develop a data infrastructure for future Artemis missions. The following details results of Phase I efforts in which we address Aims 1 and 2 to develop an unobtrusive measurement plan and coding scheme to capture key constructs, contributing factors, and performance decrements across each risk area. METHOD As part of Phase I, we conducted an interdisciplinary literature review and consulted with SMEs to identify unobtrusive methodologies that leverage text, audio, and/or video data as well as conceptualize key performance metrics, contributing factors, and BMed, Team, HSIA, and Sleep risk constructs related to performance decrements. The Phase I effort resulted in a finalized pre- and post-mission protocol for Artemis II, along with a measurement and coding scheme for in-mission Artemis II data. Phase II will involve data collection from the upcoming Artemis II mission. Phase III will include data processing, coding, depiction, analysis, and report writing of the Artemis II data. RESULTS & DISCUSSION To date, we have completed Phase I efforts. Specifically, we identified BMed, Team, HSIA, and Sleep risk constructs related to performance metrics, summarized how these constructs can be measured using audiovisual data collected during the mission, and worked with NASA’s HFBP Element to finalize a data collection protocol that leverages audiovisual input from the Orion spacecraft system. Our protocol includes novel unobtrusive methodologies that adhere to in-mission data streams and subsequent constraints (e.g., limited storage space on GoPro cameras, ambient noise impeding audio files) to best capture in-mission phenomena across each risk area. We will present our results from Phase I efforts, namely best practices for unobtrusive measurement as identified through literature reviews and SME consultation as well as codebook excerpts for use in Artemis II. We will include a description of planned work as we prepare for Phase II and Phase III of this research plan and the Artemis II mission itself. SUMMARY We describe progress on our Human Factors and Behavioral Performance Research for Artemis II study.

behavioral health↗
DOE OSTI2024

Underwater Target Detection Software Demonstration on the RivGen Turbine

This repository contains data and processing scripts necessary to train the object detection models utilized in the underwater target detection software demonstration on the RivGen turbine project and to produce performance metrics (precision, recall, mAP50, mAP50-95). - Contents - Data consist of "images" and "labels". Each image has an associated label, both share the same time string in its file name (e.g., 2024_05_25_09_01_57.98.jpg and 2024_05_25_09_01_57.98.txt). Time strings have the format %yyyy_%mm_%dd_%HH_%MM_%SS.%3f. Images and labels were curated from 2021 and 2024 smolt outmigration periods at the project site in Igiugig, AK. Images are monochrome 8-bit images of objects (smolt, debris, and other) passing through the field of view of the deployed cameras during various operational stages of the RivGen turbine. Labels are text files indicating the class and bounding polygon of each object in an image. The provided labels use the "YOLO" label format. - Requirements - Python3.8+ is required to install and run the train and validation script. The README.md provides instruction for installing the requirements from the requirements.py file. - Instructions - The "example_train.py" file ingests the provided data, trains a model, and produces model performance metrics at completion. NOTE: model performance metrics will vary from run to run as a consequence of the random selection of training and validation data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Energy Storage Cost and Performance Database

In support of the U.S. Department of Energy’s Energy Storage Grand Challenge, Pacific Northwest National Laboratory is applying its rich history of battery research and development to provide the U.S. Department of Energy (DOE) and industry with a guide to current energy storage costs and performance metrics for various technologies. Cost and performance metrics for individual technologies track the following to provide an overall cost of ownership for each technology: cost to procure, install, and connect an energy storage system; associated operational and maintenance costs; and end-of-life costs. These metrics are intended to support DOE and industry stakeholders in making sound decisions about future R&D directions and priorities that move the United States closer to its goal of energy independence. The technologies currently being evaluated are lithium-ion [lithium iron phosphate (LFP) and nickel manganese cobalt (NMC)] batteries, vanadium redox flow batteries, lead-acid batteries, zinc-based batteries, hydrogen energy storage, pumped storage hydropower, gravitational energy storage, compressed air energy storage, and thermal energy storage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2012

I/O Performance Characterization of Lustre and NASA Applications on Pleiades

In this paper we study the performance of the Lustre file system using five scientific and engineering applications representative of NASA workload on large-scale supercomputing systems such as NASA s Pleiades. In order to facilitate the collection of Lustre performance metrics, we have developed a software tool that exports a wide variety of client and server-side metrics using SGI's Performance Co-Pilot (PCP), and generates a human readable report on key metrics at the end of a batch job. These performance metrics are (a) amount of data read and written, (b) number of files opened and closed, and (c) remote procedure call (RPC) size distribution (4 KB to 1024 KB, in powers of 2) for I/O operations. RPC size distribution measures the efficiency of the Lustre client and can pinpoint problems such as small write sizes, disk fragmentation, etc. These extracted statistics are useful in determining the I/O pattern of the application and can assist in identifying possible improvements for users applications. Information on the number of file operations enables a scientist to optimize the I/O performance of their applications. Amount of I/O data helps users choose the optimal stripe size and stripe count to enhance I/O performance. In this paper, we demonstrate the usefulness of this tool on Pleiades for five production quality NASA scientific and engineering applications. We compare the latency of read and write operations under Lustre to that with NFS by tracing system calls and signals. We also investigate the read and write policies and study the effect of page cache size on I/O operations. We examine the performance impact of Lustre stripe size and stripe count along with performance evaluation of file per process and single shared file accessed by all the processes for NASA workload using parameterized IOR benchmark.

Saini, Subhash↗
NASA NTRS2005

A Simple, Powerful Method for Optimal Guidance of Spacecraft Formations

One of the most interesting and challenging aspects of formation guidance law design is the coupling of the orbit design and the science return. The analyst s role is more complicated than simply to design the formation geometry and evolution. He or she is also involved in designing a significant portion of the science instrument itself. The effectiveness of the formation as a science instrument is intimately coupled with the relative geoniet,ry and evolution of the collection of spacecraft. Therefore, the science return can be maximized by optimizing the orbit design according to a performance metric relevant to the science mission goals. In this work, we present a simple method for optimal formation guidance that is applicable to missions whose performance metric, requirements, and constraints can be cast as functions that are explicitly dependent upon the orbit states and spacecraft relative positions and velocities. We present a general form for the cost and constraint functions, and derive their semi-analytic gradients with respect to the formation initial conditions. The gradients are broken down into two types. The first type are gradients of the mission specific performance metric with respect to formation geometry. The second type are derivatives of the formation geometry with respect to the orbit initial conditions. The fact that these two types of derivatives appear separately allows us to derive and implement a general framework that requires minimal modification to be applied to different missions or mission phases. To illustrate the applicability of the approach, we conclude with applications to twc missims: the Magnetospheric Mu!tiscale mission (MMS), a,nd the TJaser Interferometer Space Antenna (LISA).

Hughes, Steven P.↗
NASA NTRS2006

A Simple, Powerful Method for Optimal Guidance of Spacecraft Formations

One of the most interesting and challenging aspects of formation guidance law design is the coupling of the orbit design and the science return. The analyst's role is more complicated than simply to design the formation geometry and evolution. He or she is also involved in designing a significant portion of the science instrument itself. The effectiveness of the formation as a science instrument is intimately coupled with the relative geometry and evolution of the collection of spacecraft. Therefore, the science return can be maximized by optimizing the orbit design according to a performance metric relevant to the science mission goals. In this work, we present a simple method for optimal formation guidance that is applicable to missions whose performance metric, requirements, and constraints can be cast as functions that are explicitly dependent upon the orbit states and spacecraft relative positions and velocities. We present a general form for the cost and constraint functions, and derive their semi-analytic gradients with respect to the formation initial conditions. The gradients are broken down into two types. The first type are gradients of the mission specific performance metric with respect to formation geometry. The second type are derivatives of the formation geometry with respect to the orbit initial conditions. The fact that these two types of derivatives appear separately allows us to derive and implement a general framework that requires minimal modification to be applied to different missions or mission phases. To illustrate the applicability of the approach, we conclude with applications to two missions: the Magnetospheric Multiscale mission (MMS) , and the Laser Interferometer Space Antenna (LISA).

Hughes, Steven P.↗
NASA NTRS2007

Stretched Lens Array Squarerigger (SLASR) Technology Maturation

Since April 2005, our team has been underway on a competitively awarded program sponsored by NASA s Exploration Systems Mission Directorate to develop, refine, and mature the unique solar array technology known as Stretched Lens Array SquareRigger (SLASR). SLASR offers an unprecedented portfolio of performance metrics, SLASR offers an unprecedented portfolio of performance metrics, including the following: Areal Power Density = 300 W/m2 (2005) - 400 W/m2 (2008 Target) Specific Power = 300 W/kg (2005) - 500 W/kg (2008 Target) for a Full 100 kW Solar Array Stowed Power = 80 kW/cu m (2005) - 120 kW/m3 (2008 Target) for a Full 100 kW Solar Array Scalable Array Capacity = 100 s of W s to 100 s of kW s Super-Insulated Small Cell Circuit = High-Voltage (300-600 V) Operation at Low Mass Penalty Super-Shielded Small Cell Circuit = Excellent Radiation Hardness at Low Mass Penalty 85% Cell Area Savings = 75% Lower Array Cost per Watt than One-Sun Array Modular, Scalable, & Mass-Producible at MW s per Year Using Existing Processes and Capacities

O'Neill, Mark↗
DOE OSTI2025

Evaluating Tools and Technologies for Monitoring Baleen Whales During Offshore Wind Foundation Installation

Impacts to baleen whales are of particular concern in the context of offshore wind development because of their conservation status, the overlap of their habitat with current and planned offshore wind energy facilities, and their expected sensitivity to low-frequency sounds, such as those produced during pile driving. Therefore, this report focuses on monitoring technologies capable of detecting this species group. The scope of this report is to assess the current state of technologies and methods for monitoring baleen whales in low- and no-light conditions in conjunction with offshore wind foundation installation. This work considers the performance of various sensing technologies that can be used to observe the presence of baleen whales near offshore construction activities. The scope of work includes: 1. Technology Performance Metrics – Identify metrics that can be used to assess technology performance. 2. Technology Evaluation – Synthesize the past performance of technologies with respect to the performance metrics based on available literature. 3. Technology Characterization Framework – Describe a potential framework to characterize technology performance with a standardized approach. 4. Technology Research and Development Needs – Identify future needs and opportunities for research, development, and deployment to improve technologies.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Experimental and Numerical Investigation of the NASA High Efficiency Centrifugal Compressor Vaned Stage Geometry and Aerodynamic Performance

Since its inception in the early 2010s, the NASA High Efficiency Centrifugal Compressor (HECC) has been enigmatic for the propulsion research community: experimental data and numerical simulations of the stage have generally not aligned in their quantifications of performance metrics. Typically, the fault for these disagreements is assigned to the numerical simulations as the simulations are models, and models are inherently incomplete representations of the experiment. This “incompleteness” may manifest in assumptions regarding roughness or heat transfer, simplifications of the flow path (i.e., neglecting bleed flows), or the oft-scapegoated turbulence model. In the case of HECC, recent work showed unexpected discrepancies between the intended impeller geometry defined in the design report (termed Design-Intent) and the manufactured impeller used in the experimental campaigns (termed As-Manufactured). That work used numerical simulations to establish that the geometric differences between the Design-Intent and As-Manufactured impellers were significant enough to result in drastically different performance predictions for the HECC vaneless diffuser configuration. The Design-Intent impeller simulations over predicted the performance relative to the experiment, whereas the As-Manufactured simulations better represented the experimental data, both in terms of one-dimensional performance metrics and spanwise flow profiles. This effort expands on that work by examining in detail the geometry and aerodynamic performance of the HECC vaned diffuser configuration. Further differences between the Design-Intent and As-Manufactured geometries have been discovered in the vaned diffuser and exit guide vanes, and these differences are documented herein. The summations of the geometric differences for all of the components were used to create two numerical models of HECC vaned diffuser configuration: the Design-Intent simulations which are generated from the original geometry definitions given in the design report and the As-Manufactured simulations which are the best available representation of the manufactured compressor hardware used in the experimental test campaigns. In congruence with the earlier vaneless diffuser work, the numerical predictions of the Design-Intent choked mass flow rate, total pressure ratio, and efficiency were notably greater than that of the As-Manufactured simulations. To increase confidence in the experimental dataset, measurements from a recent test campaign conducted in 2024 are used to validate the original experimental data acquired from 2012 to 2014 with good repeatability overall, especially considering the passage of time and differences in the data acquisition systems between the test campaigns. Both numerical simulations were then extensively evaluated against the experimental data. The As-Manufactured simulations provided better estimates of the stage performance than the Design-Intent cases in terms of most performance metrics. Nonetheless, more detailed results still show opportunities for improvement. Despite a more accurate representation of the physical hardware, characterization of the impeller work input remains a challenge even for rigorously developed numerical models.

vaned diffuser↗