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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗
NASA NTRS1991

Human factors of flight-deck checklists: The normal checklist

Although the aircraft checklist has long been regarded as the foundation of pilot standardization and cockpit safety, it has escaped the scrutiny of the human factors profession. The improper use, or the non-use, of the normal checklist by flight crews is often cited as the probable cause or at least a contributing factor to aircraft accidents. An attempt is made to analyze the normal checklist, its functions, format, design, length, usage, and the limitations of the humans who must interact with it. The development of the checklist from the certification of a new model to its delivery and use by the customer are discussed. The influence of the government, particularly the FAA Principle Operations Inspector, the manufacturer's philosophy, the airline's culture, and the end user, the pilot, influence the ultimate design and usage of this device. The effects of airline mergers and acquisitions on checklist usage and design are noted. In addition, the interaction between production pressures and checklist usage and checklist management are addressed. Finally, a list of design guidelines for normal checklists is provided.

Degani, Asaf↗
DOE OSTI2023

Mesoscale convective systems in the third pole region: Characteristics, mechanisms and impact on precipitation

The climate system of the Third Pole region, including the (TP) and its surroundings, is highly sensitive to global warming. Mesoscale convective systems (MCSs) are understood to be a vital component of this climate system. Driven by the monsoon circulation, surface heating, and large-scale and local moisture supply, they frequently occur during summer and mostly over the central and eastern TP as well as in the downstream regions. Further, MCSs have been highlighted as important contributors to total precipitation as they are efficient rain producers affecting water availability (seasonal precipitation) and potential flood risk (extreme precipitation) in the densely populated downstream regions. The availability of multi-decadal satellite observations and high-resolution climate model datasets has made it possible to study the role of MCSs in the under-observed TP water balance. However, the usage of different methods for MCS identification and the different focuses on specific subregions currently hamper a systematic and consistent assessment of the role played by MCSs and their impact on precipitation over the TP headwaters and its downstream regions. Here, we review observational and model studies of MCSs in the TP region within a common framework to elucidate their main characteristics, underlying mechanisms, and impact on seasonal and extreme precipitation. We also identify major knowledge gaps and provide suggestions on how these can be addressed using recently published high-resolution model datasets. Three important identified knowledge gaps are 1) the feedback of MCSs to other components of the TP climate system, 2) the impact of the changing climate on future MCS characteristics, and 3) the basin-scale assessment of flood and drought risks associated with changes in MCS frequency and intensity. A particularly promising tool to address these knowledge gaps are convection-permitting climate simulations. Therefore, the systematic evaluation of existing historical convection-permitting climate simulations over the TP is an urgent requirement for reliable future climate change assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

FPGA-based HPC accelerators: An evaluation on performance and energy efficiency

Hardware specialization is a promising direction for the future of digital computing. Reconfigurable technologies enable hardware specialization with modest non-recurring engineering cost, but their performance and energy efficiency compared to state-of-the-art processor architectures remain an open question. In this article, we use FPGAs to evaluate the benefits of building specialized hardware for numerical kernels found in scientific applications. In order to properly evaluate performance, we not only compare Intel Arria 10 and Xilinx U280 performance against Intel Xeon, Intel Xeon Phi, and NVIDIA V100 GPUs, but we also extend the Empirical Roofline Toolkit (ERT) to FPGAs in order to assess our results in terms of the Roofline model. We show design optimization and tuning techniques for peak FPGA performance at reasonable hardware usage and power consumption. As FPGA peak performance is known to be far less than that of a GPU, we also benchmark the energy efficiency of each platform for the scientific kernels comparing against microbenchmark and technological limits. Results show that while FPGAs struggle to compete in absolute terms with GPUs on memory- and compute-intensive kernels, they require far less power and can deliver nearly the same energy efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1

Abstract Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).

Wang, Jiaxin (ORCID:0000000348085085)↗
DOE OSTI2021

U.S.-China Clean Energy Research Center Building Energy Efficiency (CERC-BEE) Open-Source Retrofit Targeting Tool (CRADA FP00007338 Final Report)

To increase the cost-saving energy and carbon dioxide (CO 2 ) emissions reductions in buildings and portfolios at the scale and speed necessary to limit climate change, researchers at LBNL and Johnson Controls (JCI) developed the Building Efficiency Targeting Tool for Energy Retrofits (BETTER). BETTER is a software tool that consists of three components: (1) the BETTER analytical engine source code (which was developed with intellectual property provided by JCI under CRADA FP00007338); (2) the BETTER web application, developed by LBNL and McQuillen Interactive Pty. Ltd; and (3) the BETTER application programming interface (API), also developed by LBNL and McQuillen Interactive Pty. Ltd. BETTER enables building and portfolio owners, managers, and service providers worldwide to quickly, easily identify cost-saving energy efficiency retrofits in existing buildings and portfolios without expensive site visits or complex modeling. With minimal data input, the tool benchmarks a building’s electric and fossil energy usage against peers; quantifies energy, cost and greenhouse gas (GHG) emission reduction potentials at the building and portfolio levels; and recommends energy efficiency measures to decarbonize and electrify buildings and portfolios, targeting specific energy savings levels. No other tool so comprehensively analyzes buildings and portfolios with such ease. If fully implemented, it is estimated that BETTER could help reduce emissions equivalent to planting 1.3 billion trees globally by 2030. Moreover, an additional 50-75% of embodied GHG emissions could be avoided in each case where BETTER results in a building being retrofitted instead of demolished and replaced, providing substantial additional decarbonization benefits for the buildings sector. BETTER has garnered multiple awards and avid interest from investors. In 2020, it earned a R&D 100 Award for innovation and a LBNL Director’s Award for Technology Transfer. In 2021, BETTER was named an EarthX E-Capital Summit Climate Tech Prize semi-finalist

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Solar Panel Installation at Goucher College

As part of our multi-phased sustainability initiative, Goucher College is implementing a series of necessary changes to become a model “green” campus. This comprehensive approach includes implementing systems designed to reduce energy consumption, water usage, and waste production by 2030. The first phase of this holistic endeavor is to develop two independent solar projects. One will be on the Facility Management Services building (FMS) and the other will be on the Central Utility Plan (CUP). The anticipated duration of this project is expected to be 24 months. When completed, the new photovoltaic panels (PVPs) and resulting solar array system will help offset campus energy consumption. The projects will also help the College achieve its goal of working towards operating primarily on renewable energy. During initial review of the project, it was revealed replacing the roofs prior to installing new PVPs would not only provide a sound structural foundation for the projects, but the new roofing systems will also aid de-carbonization. The project’s scope is divided between two buildings. Building A: FMS is the first building and Building B: CUP is the second building.

14 SOLAR ENERGY↗
NASA NTRS1980

Automatic control of NASA Langley's 0.3-meter cryogenic test facility

Experience during the past 6 years of operation of the 0.3-meter transonic cryogenic tunnel at the NASA Langley Research Center has shown that there are problems associated with efficient operation and control of cryogenic tunnels using manual control schemes. This is due to the high degree of process crosscoupling between the independent control variables (temperature, pressure, and fan drive speed) and the desired test condition (Mach number and Reynolds number). One problem has been the inability to maintain long-term accurate control of the test parameters. Additionally, the time required to change from one test condition to another has proven to be excessively long and much less efficient than desirable in terms of liquid nitrogen and electrical power usage. For these reasons, studies have been undertaken to: (1) develop and validate a mathematical model of the 0.3-meter cryogenic tunnel process, (2) utilize this model in a hybrid computer simulation to design temperature and pressure feedback control laws, and (3) evaluate the adequacy of these control schemes by analysis of closed-loop experimental data. This paper will present the results of these studies.

Thibodeaux, J. J.↗
NASA NTRS1985

User's guide to STIPPAN: A panel method program for slotted tunnel interference prediction

Guidelines are presented for use of the computer program STIPPAN to simulate the subsonic flow in a slotted wind tunnel test section with a known model disturbance. Input data requirements are defined in detail and other aspects of the program usage are discussed in more general terms. The program is written for use in a CDC CYBER 200 class vector processing system.

Kemp, W. B., Jr.↗
DOE OSTI2025

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗
DOE OSTI2024

GQuEST Control System Resolution

GQuEST (Gravity from Quantum Entanglement of Space-Time), is a collaboration verifying a quantum gravity model by measuring holographic effects on a microscopic scale. Its interferometer apparatus filters excessive optical noise and requires a control system that can adjust the filtration to accommodate for frequency changes in the output light. We stress-test this control system by simulating filter behaviors with parameters in their outermost regimes, and we have determined a threshold that maintains precision while minimizing resource usage. These results are important for the successful operation of GQuEST's interferometer, enabling more accurate tests of quantum gravity models and thereby advancing our understanding of gravity at the quantum mechanical level.

Nguyen, David↗
NASA NTRS2011

Fuel Burn Estimation Using Real Track Data

A procedure for estimating fuel burned based on actual flight track data, and drag and fuel-flow models is described. The procedure consists of estimating aircraft and wind states, lift, drag and thrust. Fuel-flow for jet aircraft is determined in terms of thrust, true airspeed and altitude as prescribed by the Base of Aircraft Data fuel-flow model. This paper provides a theoretical foundation for computing fuel-flow with most of the information derived from actual flight data. The procedure does not require an explicit model of thrust and calibrated airspeed/Mach profile which are typically needed for trajectory synthesis. To validate the fuel computation method, flight test data provided by the Federal Aviation Administration were processed. Results from this method show that fuel consumed can be estimated within 1% of the actual fuel consumed in the flight test. Next, fuel consumption was estimated with simplified lift and thrust models. Results show negligible difference with respect to the full model without simplifications. An iterative takeoff weight estimation procedure is described for estimating fuel consumption, when takeoff weight is unavailable, and for establishing fuel consumption uncertainty bounds. Finally, the suitability of using radar-based position information for fuel estimation is examined. It is shown that fuel usage could be estimated within 5.4% of the actual value using positions reported in the Airline Situation Display to Industry data with simplified models and iterative takeoff weight computation.

Chatterji, Gano B.↗
NASA NTRS2008

Calculations of High-Temperature Jet Flow Using Hybrid Reynolds-Average Navier-Stokes Formulations

Two multiscale-type turbulence models are implemented in the PAB3D solver. The models are based on modifying the Reynolds-averaged Navier Stokes equations. The first scheme is a hybrid Reynolds-averaged- Navier Stokes/large-eddy-simulation model using the two-equation k(epsilon) model with a Reynolds-averaged-Navier Stokes/large-eddy-simulation transition function dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier Stokes model in which the unresolved kinetic energy parameter f(sub k) is allowed to vary as a function of grid spacing and the turbulence length scale. This parameter is estimated based on a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for partially averaged Navier Stokes. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The parameter f(sub k) varies between zero and one and is equal to one in the viscous sublayer and when the Reynolds-averaged Navier Stokes turbulent viscosity becomes smaller than the large-eddy-simulation viscosity. The formulation, usage methodology, and validation examples are presented to demonstrate the enhancement of PAB3D's time-accurate turbulence modeling capabilities. The accurate simulations of flow and turbulent quantities will provide a valuable tool for accurate jet noise predictions. Solutions from these models are compared with Reynolds-averaged Navier Stokes results and experimental data for high-temperature jet flows. The current results show promise for the capability of hybrid Reynolds-averaged Navier Stokes and large eddy simulation and partially averaged Navier Stokes in simulating such flow phenomena.

Abdol-Hamid, Khaled S.↗
NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗
NASA NTRS2016

Multi-Model Assessment of Global Hydropower and Cooling Water Discharge Potential Under Climate Change

Worldwide, 98% of total electricity is currently produced by thermoelectric power and hydropower. Climate change is expected to directly impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power. Improved understanding of how climate change may impact the availability and temperature of water resources is therefore of major importance. Here we use a multi-model ensemble to show the potential impacts of climate change on global hydropower and cooling water discharge potential. For the first time, combined projections of streamflow and water temperature were produced with three global hydrological models (GHMs) to account for uncertainties in the structure and parametrization of these GHMs in both water availability and water temperature. The GHMs were forced with bias-corrected output of five general circulation models (GCMs) for both the lowest and highest representative concentration pathways (RCP2.6 and RCP8.5). The ensemble projections of streamflow and water temperature were then used to quantify impacts on gross hydropower potential and cooling water discharge capacity of rivers worldwide. We show that global gross hydropower potential is expected to increase between +2.4% (GCM-GHM ensemble mean for RCP 2.6) and +6.3% (RCP 8.5) for the 2080s compared to 1971-2000. The strongest increases in hydropower potential are expected for Central Africa, India, central Asia and the northern high-latitudes, with 18-33% of the world population living in these areas by the 2080s. Global mean cooling water discharge capacity is projected to decrease by 4.5-15% (2080s). The largest reductions are found for the United States, Europe, eastern Asia, and southern parts of South America, Africa and Australia, where strong water temperature increases are projected combined with reductions in mean annual streamflow. These regions are expected to affect 11-14% (for RCP2.6 and the shared socioeconomic pathway (SSP)1, SSP2, SSP4) and 41-51% (RCP8.5-SSP3, SSP5) of the world population by the 2080s.

global hydrological models↗
DOE OSTI2025

Visualizing Temporal Topic Embeddings with a Compass

—Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a meaningful embedding space where changes in word usage and documents can be directly analyzed in a temporal context. This paper proposes an expansion of the compass-aligned temporal Word2Vec methodology into dynamic topic modeling. Such a method allows for the direct comparison of word and document embeddings across time in dynamic topics. This enables the creation of visualizations that incorporate temporal word embeddings within the context of documents into topic visualizations. In experiments against the current state-of-the-art, our proposed method demonstrates overall competitive performance in topic relevancy and diversity across temporal datasets of varying size. Simultaneously, it provides insightful visualizations focused on temporal word embeddings while maintaining the insights provided by global topic evolution, advancing our understanding of how topics evolve over time.

Cluster analysis↗
DOE OSTI2025

Comparison of Expert Vocabulary Usage Patterns Between Mental Health and Nonmental Health Clinicians When Diagnosing Pediatric Anxiety Disorders

Objective: To compare the utilization patterns of expert vocabulary (EVo) in diagnosing pediatric anxiety between mental health and non-mental health clinical notes from electronic health records to understand the role of Evo in informing classification and decision-making in anxiety diagnoses. Study design: We conducted a retrospective study using a cohort less than age 25 from Cincinnati Children's Hospital including 897 685 patients with 61 586 446 notes. We analyzed EVo, collected from mental health clinicians, in both mental and nonmental health notes. We compared classification accuracy using EVo-based patient-level embedding from all clinical notes, mental-health notes, and nonmental health notes for 2 tasks: 1) pre-vs postdiagnosis anxiety patients, and 2) prediagnosis anxiety vs nonanxiety patients. Results: EVo usage was highest in prediagnosis anxiety, lower in nonanxiety, and lowest in post-diagnosis. Classification models using EVo features from all, mental-health, and non-mental health notes showed similar F1 scores for prediagnosis anxiety (0.70 ± 0.2 for 2 categories). For anxiety vs nonanxiety classification, all clinical and nonmental health notes had better F1 scores than mental-health notes (above 0.90 for 3 categories). There was a notable difference in class-wise performance across both tasks. Conclusions: There are significant differences in anxiety EVo use between mental health and nonmental health clinicians. Despite less anxiety-specific terminology, non-mental health notes still captured key aspects of patient presentations, emphasizing the importance of including all clinicians' notes in analysis. EVo's utility for anxiety classification is most effective in prediagnostic phases, suggesting the need for a dedicated diagnostic lexicon and further study before incorporating EVo into classification models.

feature engineering↗