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823 records · Page 14

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl

Battery Evaluation Profiles for X-57 and Future Urban Electric Aircraft

Battery energy density is one of the most critical design parameters for sizing all-electric aircraft, however it’s easily overestimated. Establishing the effective, usable energy density is confused by varying degrees of margin needed to account for structural and thermal management between different cell chemistry and pack designs. Therefore, a better methodology is needed to fairly compare emerging battery technologies for electric aircraft. Currently, there is a loss of critical information when vehicle trade studies are performed using “nominal” published cell-level performance metrics. Aircraft power demands rarely match these nominal power profiles, and aircraft designers lack the ability to accurately simulate the battery performance and temperature off-nominally unless the battery chemistry is well established. Conversely, battery suppliers have no generalized reference cases to publish more realistic performance metrics. This can lead to poor assumptions, such as aircraft studies assuming a fixed discharge efficiency of a battery, when in reality the usable energy in a pack is dependent on the power and thermal profile. Information needed to properly assess weight penalties for thermal management is also typically poorly characterized when assessing candidate batteries. This paper serves to better inform battery development, and similarly, provide aircraft designers with more realistic assumptions for applying knockdown margins in their designs. Detailed power and thermal performance estimates are provided, which provide a starting point for sizing power and thermal budgets using experimentally derived battery models. Results show that the X-57 battery-to-shaft efficiency is 77.3% for a particular optimized mission. Considering a 25% reserve on the battery capacity, this means that only roughly half of the original 55.3kWh ‘nominal’ pack energy can be converted to useful work during a mission. Further estimates on a clean-sheet VTOL optimization show an average 82.7% battery-to-shaft efficiency, using 98% peak efficiency inverters and 97.4% peak efficiency motors. Although higher battery efficiencies are possible, the resulting weight penalty negates improvement in vehicle performance. These trade-offs and resulting power profiles are provided as a starting point to better assess future battery designs.

Battery Electric Aircraft

Computational Fluid Dynamics at the Lewis Research Center: An Overview

Lewis is a multidisciplinary Center with strong research and development programs in aeronautical and space propulsion, power, space communications, space experiments and materials. Computational fluid dynamics (CFD) is playing an important and growing role in most of these areas. Described here is how CFD is integrated into these programs and highlights elements of the CFD activities. Examples are presented of codes developed to predict flow fields in advanced propulsion systems and several of the code validation experiments are described. The CFD effort at Lewis ranges from basic research on new and improved algorithms through code development to the application of these codes to specific engineering problems. Because of the substantial improvement in CFD's predictive capability, its use at Lewis is on a steep growth path, spreading rapidly into new areas which had not traditionally taken advantage of the techniques of numerical simulation. Multidisciplinary codes and the future direction of CFD at Lewis are discussed.

Robert M Stubbs

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl

Harness Thermal Heat Loss Measurement for a Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

Thermal

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics

Next-Generation Hard X-ray Missions: SuperHERO and HEROIX

High-energy X-ray observations have transformed our understanding of astrophysical systems where non-thermal processes dominate, from shock-accelerated particles in supernova remnants to relativistic jets and hot coronae in active galactic nuclei. NuSTAR’s pioneering focusing images of the hard X-ray sky have demonstrated the immense scientific potential of this band, while also highlighting how limited angular resolution constrains our ability to fully characterize complex physical processes in faint extended sources and resolving faint sources in crowded sky regions. In this presentation, I will discuss a pathway to overcome these challenges through NASA Marshall Space Flight Center’s replicated NiCo full-shell X-ray mirror technology. Specifically, I will discuss the SuperHERO hard X-ray telescope to achieve better than 10-arcsecond half-power diameter (HPD) angular resolution on a balloon flight observing the Crab Nebula, and the High EneRgy Observatory for Imaging X-rays (HEROIX) Medium-Class Mission concept to achieve an integrated effective area of 570 cm2 at 30 keV with 5 arcsec HPD angular resolution.

AGN

The Significance of Water Vapor Isotopes in Improving Weather Prediction

Water vapor isotopes carry the integrated history of evaporation, condensation, mixing, and transport. Although previous studies have shown potential to improve forecasts under controlled conditions, real-world applications have been limited by systematic biases in both models and satellite retrievals arising from sparse measurements in the free troposphere. Here we assimilate mid‑tropospheric δD retrievals (peak sensitivity ~4.2 km) from the Infrared Atmospheric Sounding Interferometer into the Isotope‑incorporated Global Spectral Model and evaluate the added value beyond co‑assimilated temperature and specific humidity with identical spatial and temporal coverage. Assimilating δD improves 0–120 h forecasts of wind, temperature, specific humidity, and geopotential height, with the largest gains in the midlatitudes; heavy‑precipitation skill also increases for thresholds >3 mm per 6 h. Demonstrated in a coarse‑resolution configuration with limited observations, the results indicate that isotopic information strengthens transport tracking and hydrological constraints, motivating evaluation in operational high‑resolution forecasting systems.

Hydrology

Diamond-Loaded Polyimide Aerogel Scattering Filters and Their Applications in Astrophysical and Planetary Science Observations

Infrared-blocking, aerogel-based scattering filters have a broad range of potential applications in astrophysics and planetary science instruments in the far-infrared, sub-millimeter, and microwave regimes. This paper demonstrates the ability of conductively-loaded, polyimide aerogel filters to meet the mechanical and science instrument requirements for several experiments, including the Cosmology Large Angular Scale Surveyor (CLASS), the Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM), and the Sub-millimeter Solar Observation Lunar Volatiles Experiment (SSOLVE). Thermal multi-physics simulations of the filters predict their performance when integrated into a cryogenic receiver. Prototype filters have survived cryogenic cycling to 4 K with no degradation in mechanical properties. Measurement of total hemispherical reflectance and transmittance, as well as cryogenic tests of the aerogel filters in a full receiver context, allow estimates of the integrated infrared emissivity of the filters. Knowledge of the emissivity will help instrument designers incorporate the filters into future experiments in planetary science, astrophysics, and cosmology.

Kyle R Helson

Thermal Design and Thermal Vacuum Testing of the StarBurst Instrument

The StarBurst Multimessenger Pioneer is a small satellite mission serving as a wide-field gamma-ray observatory designed to capture the initial emissions of short gamma-ray bursts, electromagnetic signatures of neutron star mergers. This paper presents the final thermal design and analysis of the StarBurst Instrument, comprising the bus-to-instrument interface plate, control electronics, and twelve crystal detector units, which form the core of the mission’s science capability. The passive thermal control system design requires consideration of restrictive keep-out zones, unknown orbital parameters, and narrow temperature limits of the detectors. Also summarized is the instrument level thermal vacuum cycle test, correlated model refinements, and updated model results. Following successful completion of the instrument test campaign, the hardware was integrated with the spacecraft bus for spacecraft level testing, including additional thermal vacuum testing. The results from the spacecraft level thermal vacuum test will further inform the instrument thermal model, ensuring accurate flight temperature predictions. StarBurst launches as a secondary payload in 2027 and has a mission duration of at least one year.

StarBurst

The NERVA Engine Program

The objective of the NERVA engine program is the development of a nuclear rocket engine for use in space missions. The letters N E R V A mean Nuclear Engine for Rocket Vehicle Application. NERVA is a long-range program that had its beginning in about 1955 when the Los Alamos Scientific Laboratory began preliminary studies on the feasibility of thermal reactors for rocket application. At about the same time, the Livermore Laboratory began parallel studies, but this dual effort was discontinued about a year later. In 1961 an industrial contractor team, the Aerojet-General Corporation and the Westinghouse Electric Corporation, was selected to carry out the development of the NERVA engine, and their activity began in mid-1961. Aerojet was made the prime contractor with responsibility for the complete engine development program, and Westinghouse was made a principal subcontractor with responsibility for the development of the reactor. A government field office, the Cleveland Extension of the Space Nuclear Propulsion Office, was set up to manage this development program. This office is located in Cleveland because of the availability of technical backup at the Lewis Research Center.

Lester C Corrington

International Ultraviolet Explorer (IUE) Battery History and Performance

The "International Ultraviolet Explorer (IUE) Battery History and Performance" report provides the information on the cell/battery design, battery performance during the thirty eight (38) solar eclipse seasons and the end-of-life test data. It is noteworthy that IUE spacecraft was an in-house project and that the batteries were designed, fabricated and tested (Qualification and Acceptance) at the Goddard Space Flight Center. A detailed information is given on the cell and battery design criteria and the designs, on the Qualification and the Acceptance tests, and on the cell life cycling tests. The environmental, thermal, and vibration tests were performed on the batteries at the battery level as well as with the interface on the spacecraft. The telemetry data were acquired, analyzed, and trended for various parameters over the mission life. Rigorous and diligent battery management programs were developed and implemented from time to time to extend the mission life over eighteen plus years. Prior to the termination of spacecraft operation, special tests were conducted to check the battery switching operation, battery residual capacity, third electrode performance and battery impedance.

Rao, Gopalskrishna M.

Space Transportation System Technology Symposium. Volume 2 - Dynamics and Aeroelasticity

The Space Shuttle, being an hybrid – an airplane and a launch vehicle – represents the greatest challenge that the dynamicist and the aeroelastician have faced. Some specific problem areas related to the Space Shuttle are listed on figure 1. Dynamics and aeroelasticity envelop many disciplines, including aerodynamics, vibration, random processes, structures, fluid flow, mechanics, etc., but, of more importance, they involve the interaction and coupling of many of these various disciplines. Fundamentally, we are concerned with structural integrity and safe flight, i.e., trying to ensure that the vehicle will remain structurally intact as well as function properly in the presence of the many faceted dynamic environment. A new area which may have an impact on our task is the effect of the high temperature environment. In the past, we have been able to successfully decouple the temperature effects from our problem formulation. For the Space Shuttle, this problem must be closely reexamined. As has been pointed out in the opening remarks of the Conference, the Dynamics and Aeroelasticity Technology Group comprises one of several technology groups which are attempting to provide the necessary research to support a successful and safe vehicle. The group has members from most of the NASA Centers as well as from the Air Force groups. We meet periodically to review ongoing work, search for new problem areas; and we are constantly updating and revising our program. The group is organized into three panels as shown on figure 2: a panel on Dynamic Loads and Response, one on Aeroelasticity, and one on Flight Dynamics and Environment. The Conference papers accordingly have been grouped in these same three areas, with each Panel Chairman acting as moderator for his particular session.

Harry L Runyan

Technology Readiness Assessment for Stirling Power Convertor

Stirling-based power conversion system could represent a critical enabling technology for future NASA missions, offering significantly enhanced power efficiency over traditional thermoelectric systems. To ensure the successful infusion of this technology into deep space and planetary surface missions, a rigorous evaluation of its maturity and associated risks is essential. The objective of this Technology Readiness Assessment (TRA) is to determine the current technology readiness level (TRL) of the Stirling power convertor and identify key technical risks and challenges associated with its maturation and potential infusion into a targeted flight system. The evaluation process will rigorously follow the NASA TRA procedure: (1) determining the requirements that underpin the design, function, and performance; (2) finding and listing all new technology elements (NTEs) and critical technology elements (CTEs); (3) identifying the level of integration assumed for the assessment; and (4) assessing the TRL for each NTE and CTE. The overall subassembly TRL will then be determined via a roll-up using the “weakest link” criterion, culminating in a final (5) assessment of risks to further progression of maturity. This paper will present the results of a comprehensive technology readiness assessment (TRA) conducted on the Stirling-based dynamic power conversion subassembly, excluding the radioisotope heat source. The paper will also describe a detailed breakdown of the TRL roll-up and a matrix of identified risks and recommended mitigation paths, along with identified key technical risks and challenges to achieve the required long-duration performance. Key Words: Radioisotope Power Conversion, Technology Readiness Assessment

Radioisotope Power Conversion

Development, Characterization, and Validation of Elevated-Temperature Constitutive Models: Deformation and Damage

This report provides a brief review of experimentally observed hereditary and nonhereditary material behavior along with background information on standard as well as advanced internal state variable constitutive modeling at elevated temperature. A description of exploratory, characterization, and validation testing is presented along with a detailed outline of what constitutes “sufficient” data content (i.e., quality and quantity) for developing or enhancing, characterizing, and validating a particular sophisticated nonlinear time- and history-dependent (hereditary) class of constitutive models known as GVIPS (generalized viscoplasticity with potential structure). The tests described are necessary to reveal a material’s behavior in the reversible (or viscoelastic) and irreversible (or viscoplastic) regimes, for the identification of both deformation and damage model parameters. Results presented are primarily for metallic materials. In all cases, both uniaxial and multiaxial tests are described, and the linkage between the specific tests and the parameters within the model that can be characterized from the results of these tests are also discussed. Discussion is also provided relative to the role information management must play relative to material data collection, analysis, maintenance, and dissemination. The need for such an information system is particularly important as both analyst and designer move toward utilizations of sophisticated, nonlinear time- and history dependent (hereditary) constitutive models. Lastly, the concept of state space and its utility in understanding and establishing constitutive models is addressed throughout. The intent behind this document is to help both the modeler and experimentalist understand each other’s specific points of view and provide guidance for both model development and characterization. Emphasis has been placed on providing the mechanician with information regarding how tests are performed and what issues to be aware of when interpreting results. It is hoped that experimentalists will take away a new perspective on the types of information that modelers and analysts are looking for from them.

Constitutive Modeling