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  Join us for an in-depth webinar on the technical challenges of Overhead Persistent Infrared (OPIR) surveillance and how synthetic imagery is enhancing deep learning performance for detecting ground-based targets fr|om space-based platforms. OPIR sensors aboard satellites offer powerful capabilities for Earth observation in the thermal infrared spectrum (MWIR and LWIR), but challenges like atmospheric interference and limited image resolution make it difficult to detect, differentiate, and identify ground targets with confidence. This session explores how synthetic EO/IR datasets—generated using MuSES and CoTherm—can supplement real-world data to improve training for machine learning algorithms in these demanding conditions. We’ll present a case study using YOLO (“You Only Look Once”) deep learning models trained on synthetic datasets of adversarial ground vehicles across varying weather conditions, times of day, and operational states. The webinar will emphasize how image resolution impacts detection and recognition performance, offering insights into how future high-resolution space sensors might enhance OPIR effectiveness. What You’ll Learn: Challenges in OPIR surveillance and data acquisition in the IR spectrum How synthetic data generation supports robust training for ML algorithms Use of MuSES and CoTherm to simulate realistic thermal IR overhead imagery Impact of image resolution on YOLO algorithm performance Implications for future space-based sensor system design Who Should Attend: Professionals and researchers in remote sensing, aerospace defense, EO/IR imaging, and AI/ML applications in surveillance. Explore how simulation, AI, and next-generation sensing platforms intersect to shape the future of global overhead surveillance.

Electronics are increasingly critical to vehicle performance, fr|om ECUs hidden beneath the dash to ADAS cameras mounted at the windshield. These components must operate reliably across extreme thermal environments—yet traditional testing is costly, time-consuming, and often limited to late development stages. In this webinar, we will demonstrate how TAITherm and RapidFlow enable engineers to explore electronics thermal management early in the design process. We will showcase: Modeling electronics and heat-generating components in TAITherm, including power dissipation and derating behaviors. RapidFlow’s fast cabin soak simulations, capturing solar loading and transient cabin air/structure heating. HVAC cooldown analysis with RapidFlow, providing rapid iteration for design trade-offs. Methods to connect simulation to component reliability, using temperature predictions to inform derating strategies and component selection. Attendees will see how these tools deliver fast, accurate 3D transient simulations, helping engineers understand and mitigate thermal risks to electronics performance—long before physical prototypes are available. Presenter: Savannah Page is a Thermal/CFD Engineer at ThermoAnalytics, where she supports the development and validation of automotive cabin and human thermal models. She specializes in modeling clothing, human thermoregulation, automotive HVAC systems, and medical device electronics, and she developed a Python tool that streamlines human model preprocessing. Savannah has presented her work at human thermal seminars and conferences worldwide. She earned her B.S. and M.S. degrees in Biomedical Engineering fr|om Michigan Technological University before joining ThermoAnalytics in 2024.

Are you ready to revolutionize your EO/IR simulation capabilities?  Join us for an exclusive webinar exploring the cutting-edge integration of multimodal remote sensing data and human thermal modeling within MuSES — the premier simulation environment for realistic battlefield and security scenarios within the infrared (IR) spectrum. Successful human detection and recognition in complex environments demands more than just data — it requires diverse, dynamic, and realistic training sets. This webinar will reveal how incorporating variations in clothing, body pose, time of day, weather, sensor perspectives, and background scenes can enhance the robustness of AI and machine learning models in EO/IR applications.  Leverage our toolchain to create more realistic and dynamic simulations involving human subjects within MuSES. What You’ll Learn: Realistic Environmental Modeling: Accurately simulate battlefield conditions, including solar loading, atmospheric effects, and terrain interactions, seamlessly integrating various remote sensing data sources into your MuSES simulations Advanced Human Thermal Modeling: Simulate thermoregulating humans with varied poses and clothing ensembles to reflect real-world operational conditions Automatic Target Detection/Recognition: Investigate the ability to detect and recognize embedded targets in cluttered scenes and analyze the impact of adjusting key variables on performance Multimodal Dataset Generation: Discover innovative techniques to combine multiple sensor wavebands into composite false-color images, boosting alternative training strategies and AI resilience Who Should Attend: This webinar series is ideal for defense engineers, researchers, data scientists, image analysts, and program managers involved in: Intelligence, surveillance, target acquisition, and reconnaissance (ISTAR) efforts Automatic target recognition (ATR) development and evaluation Soldier vulnerability and mission planning Automated security applications Presenters: Scott Gibbs is a Senior Engineer at ThermoAnalytics, Inc., where he leads the Electro-Optical/Infrared (EO/IR) Engineering Team and oversees the development of advanced thermal and signature prediction capabilities. With over 20 years of experience in the defense industry, Scott specializes in EO/IR signature modeling, field test validation, and synthetic scene generation for applications including AI/ML and human detection. He has developed and validated thermal and IR models for a wide range of military vehicles and environments, contributed to camouflage effectiveness studies, and was a primary researcher in developing a novel 50th percentile female physiology description used in segmental human thermoregulation modeling. Scott holds a B.S. in Mechanical Engineering fr|om Michigan State University and has been with ThermoAnalytics since 2014. Audrey Levanen is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where she supports defense-focused thermal and infrared modeling, synthetic data generation for AI/ML applications, and human comfort simulation projects. She has developed custom Python tools for automating image annotation and analyzing thermal comfort results, helping streamline workflows for both simulation and data science teams. Audrey joined ThermoAnalytics full-time in 2023 after interning with the company and earning her B.S. in Mechanical Engineering fr|om Michigan Technological University.

Join us for a technical webinar exploring how synthetic thermal infrared imagery can dramatically improve deep learning performance for detecting and recognizing unmanned aerial vehicles (UAVs). In the thermal IR wavebands (MWIR and LWIR), acquiring large, high-quality datasets—especially of adversarial targets—can be difficult. This session will highlight how physics-based simulation tools like MuSES and CoTherm are used to generate realistic, diverse datasets of commercial and military UAVs under varying weather conditions, times of day, and sensor perspectives. We’ll discuss the automated generation of these synthetic datasets and demonstrate their impact on training a YOLO (“You Only Look Once”) deep learning model. Performance will be analyzed across real and synthetic imagery, examining how variables like background conditions and resolution affect detection and recognition accuracy. What You’ll Learn: Challenges of training deep learning models in thermal IR How to simulate realistic UAV thermal signatures with MuSES Automation of dataset generation and image processing with CoTherm Comparative performance of YOLO on real vs. synthetic IR imagery Who Should Attend:Engineers, data scientists, researchers, and defense technologists working with thermal imaging, machine learning, or UAV detection. Don't miss this opportunity to see how simulation and AI combine to solve real-world sensing challenges. Presenters: Logan Canull is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where he supports research and development efforts focused on advancing the thermal modeling of lithium-ion batteries. His work includes expanding ThermoAnalytics’ battery library, developing methods to simulate thermal runaway propagation, and investigating battery cooling strategies using RapidFlow. Logan also contributes to energy usage estimation projects that integrate photovoltaics, HVAC systems, and human comfort modeling. He joined ThermoAnalytics in 2022 after earning his B.S. in Mechanical Engineering fr|om Michigan Technological University and completed his M.S. in Mechanical Engineering in 2023. J. Weston Early is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where he applies his background in simulation, heat transfer, computer vision, and algorithm design to support research and modeling efforts. With dual bachelor’s degrees in Mechanical Engineering / Engineering Mechanics and Computer Engineering fr|om Michigan Technological University, Weston brings a multidisciplinary perspective to thermal analysis, image processing, and data-driven simulation. His skill set spans software development, statistical analysis,  3D modeling, and closed loop control systems, making him well-suited to support work involving synthetic data generation and AI-driven thermal modeling.

Join us for an insightful webinar exploring the cutting-edge scene simulation capabilities of MuSES (Multi-Service Electro-Optic Signature) and the transformative potential of AI/ML for defense applications. Training robust machine learning algorithms for defense applications often requires vast amounts of accurately labeled real-world data, which can be expensive and time-consuming to obtain, especially for non-visible wavebands. Synthetic imagery offers a powerful and appropriate alternative for generating sufficiently large and diverse image datasets for training purposes. In this session, you'll discover how MuSES provides unparalleled accuracy in simulating ground vehicles, manned and autonomous fixed-wing and rotary aircraft, watercraft, human personnel and other high-fidelity targets in realistic operational environments. We'll walk through its powerful features for: Realistic Environmental Modeling: Accurately simulate battlefield conditions, including solar loading, atmospheric effects, and terrain interaction. Detailed Thermal-Electrical Modeling: Incorporate electronic heat sources, coupled battery and photovoltaic power systems, phase change materials and other sophisticated target details. Human Modeling: Include thermoregulating humans with realistic poses and clothing into scenes. Signature Management: Explore the impact of optical surface properties and thermal management systems on the detectability of targets in cluttered scenes. Automatic Target Detection/Recognition: Investigate the ability to detect and recognize embedded targets in cluttered scenes and rigorously study how the effectiveness of trained AI/ML algorithms is impacted by variables of interest. We'll explore how to integrate AI/ML techniques with MuSES by synthetically creating large sets of training data with the desired level of detail/resolution and variation. An extensive database of 3D target models exists (including ground vehicles, maritime vessels, aircraft, human personnel, etc.) with accurate geometric features, optical surface properties, and internal heat sources (e.g., engine, exhaust, and electronics). Learn how these target models can be combined with background scenes to: Rapidly evaluate numerous operational scenarios with automated simulation processes. Streamline data processing and extract critical insights fr|om complex simulation results. Determine how best to exploit adversarial signatures or minimize cooperative target detection. Who Should Attend: This webinar series is ideal for defense engineers, researchers, data science, image analysts, and program managers involved in: Intelligence, surveillance, target acquisition, and reconnaissance (ISTAR) efforts Vehicle system development and evaluation Soldier vulnerability and mission planning Search and rescue operations Automated security applications Presenter Bios: Eli Datema is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where he develops thermal and EO/IR models for defense and commercial applications using TAITherm, MuSES, and CoTherm. Based in the Calumet office, Eli specializes in creating high-fidelity scene simulations that support a range of use cases, including AI/ML algorithm development. He began his career at ThermoAnalytics as an intern in 2020 and joined full-time in 2021 after earning his B.S. in Mechanical Engineering fr|om Michigan Technological University. Jacob Hendrickson is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where he focuses on thermal and infrared modeling for both commercial and defense applications. He has extensive experience in full vehicle thermal validation, EO/IR scene simulation, and synthetic environment creation using MuSES, including texture mapping, terrain classification, and realistic material assignment. Jacob also supports AI/ML development through the generation of accurate scene data and target representations, and has contributed to human thermal modeling through the creation of manikin models and a novel infant physiology. He joined ThermoAnalytics in 2020 and holds a B.S. in Mechanical Engineering and an M.B.A. fr|om Michigan Technological University.

  Discover how to accurately predict the thermal and radiometric EO/IR signatures of high-value maritime targets in dynamic environments. This live webinar provides a practical demonstration of how to simulate dynamic maritime target signatures and corresponding naval countermeasures using MuSES. We will cover: Predicting physical temperatures and radiometric EO/IR signatures of high-value maritime targets using MuSES. A comprehensive overview of the simulation model approach, including environmental setup, model attribution, and dynamic inputs for engine state and vessel speed. Detailed ship exhaust fluid simulation and plume analysis. Optimizing rendering settings and showcasing example imagery and animations. Analyzing the thermal simulation and signature impact of key naval countermeasures: Ship stack suppression for exhaust plume cooling. Water wash for exterior ship surface cooling. Flare deployment for missile distraction. Who should attend: Ship design engineers – Predict and reduce ship thermal signature through simulation Naval threat analysts – Predict and exploit adversarial ship signatures Data scientists – Generate physics-based IR imagery for AI/ML threat detection Speaker Bios: Dr. Corey Packard is a Principal Engineer and Director of Research & Product Management here at ThermoAnalytics. He has more than 20 years of experience in remote sensing and physics-based simulation, with his primary technical focus being EO/IR signature prediction. Other technical efforts of Dr. Packard involve field test validations, phenomenological investigations, software development support, and predicting the behavior of optical sensor systems in turbulent atmospheres and fr|om space-based platforms. Madison Bevins is a Thermal and CFD Engineer at ThermoAnalytics. Her primary focus is in the creation and validation of thermal models for military and commercial use, using TAITherm, MuSES, and CoTherm. Madison has been with TAI since 2023, when she began as an intern while obtaining her B.S. in Biomedical Engineering fr|om Michigan Technological University. 

Fast charging is a must-have for today’s EVs, but it pushes battery systems to their thermal limits. Extreme temperatures, exacerbated by fast charging and harsh environments, can lead to premature component degradation and reduced battery lifespan.  While real-world testing in all variable conditions is limited, advanced 3D thermal simulations provide critical insights. In this webinar we’ll demonstrate how 3D thermal simulation can be carried out on various fast charging scenarios and the effect on key components. This webinar will explore: The thermal challenges associated with fast charging in EVs under cold conditions for various insulation, heating and preconditioning strategies. Methods for quantifying and mitigating thermal stress to extend battery lifetime. The impacts of various fast-charging scenarios on key battery components - bus bars and connectors. Who should attend:   Thermal and battery simulation engineers – Looking to improve or optimize battery thermal management through simulation. Automotive OEMs & Suppliers – Developing battery thermal management solutions Researchers – Developing simulation and validation methods Presenter Bio: Sacha Jelic is a Munich-based Key Account Manager at ThermoAnalytics, bringing 20 years of expertise in Aerodynamic and Thermodynamic CFD simulations. Specializing in the automotive and aerospace industries, his work encompasses engine thermal protection, brake cooling, human comfort, and battery cooling. With an MSc in Aerospace fr|om TU Delft (CFD specialization), Sacha provides technical expertise to major OEMs across Europe and Asia.

Ensuring clear windshield and side window visibility in cold weather is a critical aspect of vehicle development. Traditional wind tunnel and cold chamber testing can be costly and time-intensive, making simulation a powerful alternative for validating defrost performance, as well as refining designs early in the development process. In this webinar, we will showcase how TAITherm enables engineers to accurately simulate the phase change process and validate defrost performance, while also ensuring compliance with safety regulations. We will demonstrate how to integrate 1D HVAC models with 3D thermal/CFD simulations to assess the combined effects of airflow, glazing materials, and heating elements. Attendees will gain insights into extracting key performance metrics and leveraging various simulation workflows—fr|om high-fidelity analyses to accelerated methodologies for rapid design studies.   Key Highlights and Takeaways: Three-tool coupling for an accurate defrost solution Validating physical test requirements using TAIThermTM to extract key performance metrics required to validate the physical test requirements Demonstrating how RapidFlowTM can enable rapid design studies, with a good tradeoff between computational time and accuracy Who should attend: Thermal, HVAC, CFD, and simulation engineers – Looking to improve defrost system design and evaluate airflow, heating, and glazing interactions through simulation. Performing defrost performance validation simulations as part of a vehicle development program. Automotive OEMs & Suppliers – Developing defrost solutions / interested in design studies Researchers – Developing simulation and validation methods

Join us for a webinar exploring how clothing insulation and surface area coverage significantly influence thermal sensation and comfort. Incorrectly accounting for clothing and its variability fr|om person to person can lead to suboptimal product designs. In this session, you'll discover how to leverage TAI’s Human Thermal Clothing Manager to enhance human thermal simulations and optimize design outcomes. Key Highlights and Takeaways: Introducing the Human Thermal Clothing Manager (HTCM): Learn about our new auxiliary software tool featuring an intuitive graphical interface for browsing and selecting high-resolution clothing ensembles. Clothing Properties and Thermal Impact: Explore how HTCM-derived clothing properties affect heat and vapor transport in human thermal simulations. Comprehensive Ensemble Databases: Male and female Western clothing ensembles - “Updated Database of Clothing Thermal Insulation and Vapor Permeability Values of Western Ensembles for Use in ASHRAE Standard 55, ISO 7730, and ISO 9920”, Smallcombe et al 2021 Unisex PPE ensembles - Firefighter turn-out gear “A Database of Static Thermal Insulation and Evaporative Resistance Values of Dutch Firefighter Clothing Items and Ensembles”, Kuklane et al 2022 Custom clothing ensembles tailored to your specific needs. Live Demonstration: Watch a walkthrough of the HTCM interface, including browsing ensembles, outfitting high-resolution human thermal models, and assessing the impact of clothing insulation, coverage, and gender on thermal comfort. Who should attend: This webinar is ideal for researcher, engineers, and product designs seeking to improve the accuracy of thermal modeling and the design of thermally comfortable clothing.

Join us as we demonstrate how dynamic satellite simulation of high-fidelity orbiting objects can be performed with MuSES™, including thermal-electrical analysis and EO/IR sensor radiance prediction. In this webinar, we outline: ·       The motivation for thermal, electrical and EO/IR satellite simulation ·       A brief review of orbital physics relevant to thermal simulation with MuSES™ ·       A description of our transient simulation methodology for orbiting satellites ·       The incorporation of PV panels and multi-cell battery packs into coupled thermal-electric MuSES™ simulations ·       An approach to predicting battery lifetime and PV degradation during multi-year orbital missions ·       Thermal and EO/IR radiometric signature results for a communications satellite in both LEO and GEO scenarios ·       Sensitivity of radiometric EO/IR satellite signature to optical surface properties, operational state and other model parameters

Vehicle cabin simulations using high-fidelity 3D modeling techniques are powerful design tools for assessing heating or cooling performance, energy efficiency, thermal comfort of occupants, local comfort affectors, and novel control strategies. These assessments frequently require transient modeling of all modes of heat transfer outside and inside the cabin. Cabin interior details will often depend on both 3D heat transfer and fluid dynamics during cabin pre-conditioning and operation. TAIThermTM and the RapidFlowTM extension provide a powerful new technique for cabin applications with 3D physics-based airflow simulation and automatic thermal-fluid coupling with minimal pre-processing and a flexible level of detail.Join us as we explore using TAIThermTM and RapidFlowTM for cabin analysis and how this new technique complements and compares to other thermal-fluid analysis processes. This webinar will include best practices for cabin soak/pre-conditioning and warmup/cool-down, trade-offs between accuracy and efficiency, and a variety of cabin example simulations.

Join us as we demonstrate how transient battery thermal runaway simulations that include internal heat generation, cell venting, and hot gas impingement can be achieved using TAITherm™, CoTherm™, and Star-CCM+. In this webinar, we discuss: • Predicting physical battery temperatures with TAITherm™, our state-of-the-art simulation tool, coupled with Star-CCM+ using CoTherm™ to include the effects of cell venting and hot gas impingement.• How different internal cell heating models can be used and calibrated to test data.• Intra- and Inter-cell propagation rate validations.• A case study showing coupled thermal-CFD simulations, used to evaluate pack/module design.• A reduced-order fluid node approach to approximate CFD cell venting boundary conditions.• Internal pressure equations, implemented in TAITherm™, to predict when a cell starts venting, fluid flow rates, and venting time.

Join us as we demonstrate how MuSES™ can be used to dynamically simulate physical temperatures and predict the EO/IR sensor radiance of airborne targets.  In this webinar, we cover: Using our state-of-the-art simulation tool (MuSES™) to predict physical temperatures and EO/IR signatures of various high-value airborne targets (Aircraft and UAVs) A brief review of the physics relevant to aerial thermal simulation, including: Modeling weather at altitude Aerodynamic convection Plume modeling Hardbody considerations Simulating the sky domain and creating sensor imagery of an elevated target with a sky background Ongoing research areas related to aircraft simulation

Join us as we demonstrate how maritime targets are modeled and dynamically simulated in MuSES™, taking into account both physical temperature calculations and EO/IR sensor radiance prediction. In this webinar, we discuss: Using our state-of-the-art simulation tool, MuSES™, to predict physical temperatures and EO/IR signatures of various high-value maritime targets The process of attributing the model with the appropriate inputs, including: Environment setup Separating waterline convection parts Explore the different ways to model backgrounds, such as: Unstructured vs. Structured (faceted) sea surface Littoral background (a combination of land and sea) Rendering Settings and Examples featuring example imagery with multiple ships in-theatre Wake modeling Plume modeling including a ranger plume example

Electric vehicle (EV) energy consumption is strongly impacted by the energy used to maintain cabin, motor, and battery temperatures. Join us as we present an approach for predicting EV energy consumption based on environmental conditions where a TAIThermTM model of the vehicle and its occupants is combined with a thermal-electrical model of the battery pack and a 0D EV energy consumption model. Our TAIThermTM 3D heat transfer solver, Human Thermal extension, and thermal-electrical battery model will be used to calculate the energy needed to maintain occupant comfort and motor and battery temperatures within their optimal ranges, while the 0D model calculates the energy consumption of the motor for a specific drive cycle. We will use our process automation software CoThermTM to couple the individual models and automate the simulation runs. We will apply this approach to a city drive cycle of a representative EV in three different environments and compare the impacts of thermal management.

Join us as we demonstrate how MuSES™ and Oktal can achieve sophisticated scene simulation with large, complex backgrounds and high-resolution target models. In this webinar, we outline: Industry-standard simulation tools to predict physical temperatures and EO/IR signatures of high value targets with realistic mission profiles in natural weather environments. Industry-standard simulation tools capable of multi-modality data to predict EO/IR signatures of large, complex scenes with sophisticated sensor modeling and platform motion. A scene simulation process that allows high-resolution target models with mission-specific heating profiles and natural weather effects to be inserted into an expansive, complex background scene. A demonstration of some example coupling outcomes using MuSES™ and Oktal-SE in tandem. Database target models available for use with these EO/IR scene simulation tools. Thoughts on future MuSES™-Oktal coupling enhancements and collaborations.

Cabin HVAC design is an essential area of analysis for modern vehicles, particularly for xEV architectures where energy usage of the HVAC system is a crucial outcome. Using human occupant thermal comfort as a design target is enabled by TAITherm plus the Human Thermal Extension. There are many design considerations and variable input conditions to consider, including human factors such as physiological size, activity level, and clothing. Given the large matrix of possible inputs and the desire for efficient simulation processes, should the human position be another critical input? Join us as we explore this question using TAITherm, Human Thermal, and RapidFlow. We will look at three different human positions in a cabin cool-down scenario and analyze the results to determine whether position affects sensation and comfort. Considering the study results, we will conclude with best practices for setting up cabin simulations for energy and comfort analysis.

Simulation engineers encounter a significant challenge in balancing designing vehicles for optimal cabin comfort and achieving a harmonious blend of high energy efficiency and maximum battery range. ThermoAnalytics® has addressed this challenge by developing comprehensive cabin modeling techniques. These tools aid in assessing energy consumption by incorporating dynamic heating, ventilation, and cooling (HVAC) control strategies, along with features for localized comfort, such as heated steering wheels, radiant panels, and seat heating/cooling, specifically designed for electric vehicles (xEV). Join us as we briefly overview various modeling techniques employed to maximize passenger comfort. Using our TAITherm™ and Human Thermal module, we'll explore these techniques at different design phases. Additionally, Volvo Cars will share insights into their thermal cabin model development approach in interior climate simulations. The presentation will demonstrate a cabin heat-up and cool-down scenario utilizing GT-TAITherm coupling, discussing the proposed solution's accuracy and efficacy.

Join us as we demonstrate how synthetic terrain creation, EO/IR scene simulation, and synthetic image generation for AI/ML applications can be achieved using MuSES™ and CoTherm™. In this webinar, we discuss: • Using our state-of-the-art simulation tool (MuSES™) to predict physical temperatures and EO/IR signatures of various high-value targets, including maritime, UAV, and human targets.• Our database of target models available for use with the MuSES™ EO/IR scene simulation tool.• Improved methods for generating high-fidelity synthetic scene backgrounds at any location, which can be used to enhance the realism of synthetic EO/IR imagery.• An updated, automated CoTherm™-based scene simulation process that enables the creation of annotated EO/IR image datasets of high-resolution target models in all battlefield domains.• Effectiveness of synthetically trained AI/ML algorithms when tested with measured and synthetic images.