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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Systems integration of lunar Campsite vehicles

This paper describes the configuration design and subsystems integration resolution for lunar Campsite vehicles and the crew vehicles (CVs) which support them. This concept allows early return to the moon while minimizing hardware development. Once in place, the Campsite can be revisited for extended periods. Configuration and operations issues are addressed, and explanations of the parametric subsystem analysis, as well as descriptions of the hardware concept and performance data, are provided. Within an assumed set of launch and mission constraints, a common vehicle stage design for both the Campsite and the CV landers was the chief design driver. Accommodation of a heat-shielded, ballistic crew transportation/return vehicle, scars for later system growth and upgrades, landing the crew in close proximity to the Campsite, and appropriate kinds of robotic systems were all secondary design drivers. Physical integration of the crew module and airlock, structural system, thermal radiators, power production and storage systems, external life support consumables, and payloads are covered. The vehicle performance data were derived using a Boeing lunar transportation sizing code to optimize vehicle stage sizes and commonality. Configuration trades were conducted and detailed sketches were produced.

Capps, Stephen↗
NASA NTRS2017

Wavenumber-frequency Spectra of Pressure Fluctuations on a Generic Space Vehicle Measured via Unsteady Pressure-Sensitive Paint

Time histories of pressure fluctuations on a generic, hammerhead space vehicle model were measured using unsteady Pressure-Sensitive Paint (uPSP). The test was conducted in the 11-foot transonic wind tunnel of NASA Ames Research Center over a Mach number range of 0.6 M 1.2, and angles of attack of -4 4. The model was coated with a porous binder and PtTFPP-based porous polymer paint. An elaborate system of four high-speed cameras, and forty LED lamps was used for image acquisition. Various steps for image registration, reduction of shot noise, photogrammetry procedure to map images from the four cameras on a grid for the model, and finally a calibration procedure to convert the measured fluctuations in light intensity to fluctuating pressure, are discussed in the paper. The calibration process using a set of unsteady pressure sensors mounted on the model, was found to overcome some of the inherent problems of the fast response paint, such as rapid photo-degradation, non-linearity in pressure response, and significant temperature sensitivity. Comparison of spectra of pressure fluctuations between UPSP and pressure sensors demonstrated the ability of the paint to faithfully follow fluctuations up to 10 kHz, the maximum attempted. It was also found that the camera bit-depth and the illumination level limited the lowest measurable levels of pressure fluctuations to around 140dB. The large data set exposed various critical transonic flow physics not seen before, such as a coupling of the shock motion on the Payload Fairing (PF) with the separated flow region on the upper stage of the launch vehicle, and upstream convection of pressure fluctuation on PF at certain Mach numbers. The data also confirmed the expectation of a general lowering of the coefficient of pressure fluctuation with Mach number. The availability of the data set on a dense, regularly-spaced, surface grid allowed for the calculation of wavenumber-frequency (k-) spectra via straightforward applications of Fourier transform. The k- spectra were compared for the separated flow regions on the Second Stage, and the shock-boundary layer interactions on PF. The former showed self-similarity with Mach number while the latter was distinctly different, and confirmed the upstream propagation of pressure fluctuations. The k- spectra were dominated by the convected fluctuations; the acoustic domain was not discernable. These data, valuable for the vibro-acoustics analysis of aerospace vehicles, are believed to be the first obtained for the transonic flight regime, and pave the path for application on production models of aerospace vehicles.

buffet↗
DOE OSTI2017

Gas Gun Model and Comparison to Experimental Performance of Pipe Guns Operating with Light Propellant Gases and Large Cryogenic Pellets

Injection of multiple large (~10 to 30 mm diameter) shattered pellets into ITER plasmas is presently part of the scheme planned to mitigate the deleterious effects of disruptions on the vessel components. To help in the design and optimize performance of the pellet injectors for this application, a model referred to as “the gas gun simulator” has been developed and benchmarked against experimental data. The computer code simulator is a Java program that models the gas-dynamics characteristics of a single-stage gas gun. Following a stepwise approach, the code utilizes a variety of input parameters to incrementally simulate and analyze the dynamics of the gun as the projectile is launched down the barrel. Using input data, the model can calculate gun performance based on physical characteristics, such as propellant-gas and fast-valve properties, barrel geometry, and pellet mass. Although the model is fundamentally generic, the present version is configured to accommodate cryogenic pellets composed of H2, D2, Ne, Ar, and mixtures of them and light propellant gases (H2, D2, and He). The pellets are solidified in situ in pipe guns that consist of stainless steel tubes and fast-acting valves that provide the propellant gas for pellet acceleration (to speeds ~200 to 700 m/s). The pellet speed is the key parameter in determining the response time of a shattered pellet system to a plasma disruption event. The calculated speeds from the code simulations of experiments were typically in excellent agreement with the measured values. With the gas gun simulator validated for many test shots and over a wide range of physical and operating parameters, it is a valuable tool for optimization of the injector design, including the fast valve design (orifice size and volume) for any operating pressure (~40 bar expected for the ITER application) and barrel length for any pellet size (mass, diameter, and length). Key design parameters and proposed values for the pellet injectors for the ITER disruption mitigation systems are discussed.

Combs, Stephen Kirk↗
NASA NTRS1988

A modified ATI technique for nowcasting convective rain volumes over areas

This paper explores the applicability of the area-time-integral (ATI) technique for the estimation of the growth portion only of a convective storm (while the rain volume is computed using the entire life history of the event) and for nowcasting the total rain volume of a convective system at the stage of its maximum development. For these purposes, the ATIs were computed from the digital radar data (for 1981-1982) from the North Dakota Cloud Modification Project, using the maximum echo area (ATIA) no less than 25 dBz, the maximum reflectivity, and the maximum echo height as the end of the growth portion of the convective event. Linear regression analysis demonstrated that correlations between total rain volume or the maximum rain volume versus ATIA were the strongest. The uncertainties obtained were comparable to the uncertainties which typically occur in rain volume estimates obtained from radar data employing Z-R conversion followed by space and time integration. This demonstrates that the total rain volume of a storm can be nowcasted at its maximum stage of development.

Makarau, Amos↗
NASA NTRS1982

Association of spectral development patterns with development stages of corn

Association is made between the development stages of corn as defined by Hanway and the temporal-spectral development pattern of corn in a transformed data space derived from Landsat-MSS band reflectance values, using field-collected reflectance and associated data. Results indicate that the spectral vegetation index used (a reflectance equivalent of Tasseled Cap Greenness) reaches a maximum well before the stage at which corn is expected to achieve its peak leaf area index. Possible physiological and canopy geometry related causes for this and other results are presented.

Crist, E. P.↗
DOE OSTI2013

Bladder Cancer Patterns of Pelvic Failure: Implications for Adjuvant Radiation Therapy

Purpose: Local-regional failures (LFs) after cystectomy with or without chemotherapy are common in locally advanced disease. Adjuvant radiation therapy (RT) could reduce LFs, but toxicity has discouraged its use. Modern RT techniques with improved normal tissue sparing have rekindled interest but require knowledge of pelvic failure patterns to design treatment volumes. Methods and Materials: Five-year LF rates after radical cystectomy plus pelvic node dissection with or without chemotherapy were determined for 8 pelvic sites among 442 urothelial bladder carcinoma patients. The impact of pathologic stage, margin status, nodal involvement, and extent of node dissection on failure patterns was assessed using competing risk analysis. We calculated the percentage of patients whose sites of LF would have been completely encompassed within various hypothetical clinical target volumes (CTVs) for postoperative radiation. Results: Compared with stage {<=}pT2, stage {>=}pT3 patients had higher 5-year LF rates in virtually all pelvic sites. Among stage {>=}pT3 patients, margin status significantly altered the failure pattern whereas extent of node dissection and nodal positivity did not. In stage {>=}pT3 patients with negative margins, failure occurred predominantly in the iliac/obturator nodes and uncommonly in the cystectomy bed and/or presacral nodes. Of these patients in whom failure subsequently occurred, 76% would have had all LF sites encompassed within CTVs covering only the iliac/obturator nodes. In stage {>=}pT3 with positive margins, cystectomy bed and/or presacral nodal failures increased significantly. Only 57% of such patients had all LF sites within CTVs limited to the iliac/obturator nodes, but including the cystectomy bed and presacral nodes in the CTV when margins were positive increased the percentage of LFs encompassed to 91%. Conclusions: Patterns of failure within the pelvis are summarized to facilitate design of adjuvant RT protocols. These data suggest that RT should target at least the iliac/obturator nodes in stage {>=}pT3 with negative margins; coverage of the presacral nodes and cystectomy bed may be necessary for stage {>=}pT3 with positive margins.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.

Liu, Z.↗
NASA NTRS2003

Blade Row Interaction Effects on the Performance of a Moderately Loaded NASA Transonic Compressor Stage

Blade row interaction effects on loss generation in compressors have received increased attention as compressor work-per-stage and blade loading have increased. Two dimensional Laser Doppler Velocimeter measurements of the velocity field in a NASA transonic compressor stage show the magnitude of interactions in the velocity field at the peak efficiency and near stall operating conditions. The experimental data are presented along with an assessment of the velocity field interactions. In the present study the experimental data are used to confirm the fidelity of a three-dimensional, time-accurate, Navier Stokes calculation of the stage using the MSU-TURBO code at the peak efficiency and near stall operating conditions. The simulations are used to quantify the loss generation associated with interaction phenomena. At the design point the stator pressure field has minimal effect on the rotor performance. The rotor wakes do have an impact on loss production in the stator passage at both operating conditions. A method for determining the potential importance of blade row interactions on performance is presented.

VanZante, Dale E.↗
NASA NTRS2015

Re-Evaluation of HSE DATA in Light of High P-T Partitioning Data: Late Chondritic Addition to Inner Solar System Bodies Not Always Required for HSE

Studies of terrestrial peridotite and martian and achondritic meteorites have led to the conclusion that addition of chondritic material to growing planets or planetesimals, after core formation, occurred on Earth, Moon, Mars, asteroid 4 Vesta, and the parent body of the angritic meteorites. One study even proposed that this was a common process in the final stages of growth. These conclusions are based al-most entirely on the 8 highly siderophile elements (HSE; Re, Au, Pt, Pd, Rh, Ru, Ir, Os), which have been used to argue for late accretion of chondritic material to the Earth after core formation was complete. This idea was originally proposed because the D(metal/silicate) values for the HSE are very high (greater than 10,000), yet their concentration in the terrestrial mantle is too high to be consistent with such high Ds. The HSE in the terrestrial mantle also are present in chondritic relative abundances and hence require similar Ds if this was the result of core-mantle equilibration. The conclusion that late chondritic additions are required for all five of these bodies is based on the chondritic relative abundances of the HSE, as well as their elevated concentrations in the samples. An easy solution is to call upon addition of chondritic material to the mantle of each body, just after core formation; however, in practice this means similar additions of chondritic materials to each body just after core formation which ranges from approximately 4-5 Ma after T(sub 0) for 4 Vesta and the angrites, to 10-25 Ma for Mars, to 35 to 60 Ma for Moon and perhaps the Earth. Since the work of there has been a realization that high PT conditions can lower the partition coefficients of many siderophile elements, indicating that high PT conditions (magma ocean stage) can potentially explain elevated siderophile element abundances. However, detailed high PT partitioning data have been lacking for many of the HSE to evaluate whether such ideas are viable for all four bodies. Re-cent partitioning studies have covered P, T, fO2, and compositional ranges that allow values to be predicted at conditions relevant to these five inner solar system bodies. Because the D(HSE) metal/silicate are lowered substantially at higher PT conditions and natural com-positions (FeNi metallic liquids and peridotites) it is natural to re-examine the role of core formation on the HSE patterns in a variety of inner solar system bodies. Here I will discuss other processes (including high PT core formation for Mars, Moon and Earth) that can produce the observed HSE patterns, and demonstrate that there are viable hypotheses other than the "one size fits all" hypothesis of late chondritic additions.

Righter, K.↗
NASA NTRSDate not supplied

Predicting Fiber Failure of Plain Weave Fabric with Recursive Multiscale Micromechanics

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of machine learning models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based, modeling of material behavior at various length scales, and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using machine learning (ML) techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train machine learning models and the defining model parameters and architectures. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in for various types of machine learning models while following outlined best practices for effective data management. An effective schema for machine learning data and models can help prevent the recreation of virtual/real training data and surrogate models, can help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Failure↗
DOE OSTI2022

Utah FORGE Well 16A(78)-32 Stimulation DFN Fracture Plane Evaluation and Data

This dataset includes files used to fit planar fractures through the preliminary earthquake catalogs of the three stages of the April 2022 well 16A(78)-32 stimulation which is linked bellow. These planar features have been used to update the FORGE reference Discrete Fracture Network (DFN) model. The files are provided to encourage other modelers to use additional workflows to find additional/alternative features. To this end, the dataset includes the cleaned earthquake catalog data translated to the FORGE reference model global reference frame, the well trajectory of 16A(78)-32 in those same coordinates, the fit 15 planar features in csv format, and a pdf file with slides illustrating the process used to fit the features. A recorded presentation of this material is available from the October 2022 FORGE Modeling and Simulation Forum which is also linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer

Integration of heterogeneous data from different modalities such as genomics and radiomics is a growing area of research expected to generate better prediction of clinical outcomes in comparison with single modality approaches. To date radiogenomics studies have focused primarily on investigating correlations between genomic and radiomic features, or selection of salient features to determine clinical tumor phenotype. In this study, we designed deep neural networks (DNN), which combine both radiomic and genomic features to predict pathological stage and molecular receptor status of invasive breast cancer patients. Utilizing imaging data from The Cancer Imaging Archive (TCIA) and gene expression data from The Cancer Genome Atlas (TCGA), we evaluated the predictive power of Convolutional Neural Networks (CNN). Overall, results suggest superior performance on CNNs leveraging radiogenomics in comparison with CNNs trained on single modality data sources.

Yoon, Hong-Jun↗
DOE OSTI2025

Online Bayesian State Estimation for Real-Time Monitoring of Growth Kinetics in Thin Film Synthesis

Rapid validation of newly predicted materials through autonomous synthesis requires real-time adaptive control methods that exploit physics knowledge, a capability that is lacking in most systems. Here, in this study, we demonstrate an approach to enable real-time control of thin film synthesis by combining in situ optical diagnostics with a Bayesian state estimation method. We developed a physical model for film growth and applied the direct filter (DF) method for real-time estimation of nucleation and growth rates during pulsed laser deposition (PLD). We validated the approach using simulated and experimental reflectivity data for WSe 2 growth and ultimately deployed the algorithm on an autonomous PLD system during the growth of 1T'-MoTe 2 . The DF robustly estimates growth parameters in real time at early stages of growth, down to 15% monolayer area coverage. This fusion of in situ diagnostics, data assimilation, and physical modeling opens new opportunities in adaptive control of synthesis trajectories toward desired material states.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Reichle, Rolf H.↗
DOE OSTI2019

Indocyanine Green Fluorescence Imaging with Lymphoscintigraphy for Sentinel Node Biopsy in Melanoma: Increasing the Sentinel Lymph Node-Positive Rate

Introduction: The goal of this study was to analyze patients who underwent a sentinel lymph node biopsy (SLNB) in melanoma with the combination of radioisotope lymphoscintigraphy and indocyanine green (ICG) fluorescence imaging to compare our true positive (TP) rate, a means to perform immediate analysis of the SLNB, with that of the literature. Methods: Consecutive cutaneous melanoma patients who underwent SLNB with lymphoscintigraphy and ICG-based fluorescence imaging by the senior author (BG) from 2012 to 2018 were prospectively enrolled. The average expected SLN-positive rate per T stage was calculated based on three studies and compared with our SLN-positive rate. Results: Overall, 574 consecutive patients were analyzed. Average Breslow thickness was 1.9 mm. A total of 1754 sentinel nodes were sampled; 1497 were identified by gamma probe signaling and ICG, 241 were identified by gamma probe signaling only, and 16 were identified by ICG only. There were 123 (21.4%) patients with at least one positive SLN; 113 (91.9%) had at least one positive node identified with both gamma probe signaling and ICG, 8 (6.5%) had positive node(s) identified with gamma probe signaling only, and 2 (1.6%) had positive node(s) identified with ICG only. There was an overall 21.4% SLN-positive rate, with 8% T1, 18.5% T2, 41.1% T3, and 52.4% T4, which is higher than the predicted rates for each stage. Conclusions: With the largest cohort of patients reported who underwent a melanoma SLNB with lymphoscintigraphy and ICG, we demonstrated that this technique results in higher SLN-positive rates than predicted. Patients are being followed but, given the TP data, knowledge of our results may foster the use of this modality to improve staging and treatment options.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2010

Metabolic Rate and Ground Reaction Force During Motorized and Non-Motorized Treadmill Exercise

PURPOSE: To measure vertical ground reaction force (vGRF) and oxygen consumption (VO2) at several velocities during exercise using a ground-based version of the ISS treadmill in the M and NM modes. METHODS: Subjects (n = 20) walked or ran at 0.89, 1.34, 1.79, 2.24, 2.68, and 3.12 m/s while VO2 and vGRF data were collected. VO2 was measured using open-circuit spirometry (TrueOne 2400, Parvo-Medics). Data were averaged over the last 2 min of each 5-min stage. vGRF was measured in separate 15-s bouts at 125 Hz using custom-fitted pressure-sensing insoles (F-Scan Sport Sensors, Tekscan, Inc). A repeated-measures ANOVA was used to test for differences in VO2 and vGRF between M and NM and across speeds. Significance was set at P < 0.05. RESULTS: Most subjects were unable to exercise for 5 min at treadmill speeds above 1.79 m/s in the NM mode; however, vGRF data were obtained for all subjects at each speed in both modes. VO2 was approx.40% higher during NM than M exercise across treadmill speeds. vGRF increased with treadmill speed but was not different between modes. CONCLUSION: Higher VO2 with no change in vGRF suggests that the additional metabolic cost associated with NM treadmill exercise is accounted for in the horizontal forces required to move the treadmill belt. Although this may limit the exercise duration at faster speeds, high-intensity NM exercise activates the hamstrings and plantarflexors, which are not specifically targeted or well protected by other in-flight countermeasures.

Everett, Meghan E.↗
DOE OSTI2024

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗