CAD Model Research Articles

Geometric description of a gliding grey-headed albatross (Thalassarche chrysostoma) for computer-aided design.

Albatrosses are increasingly drawing attention from the scientific community due to their remarkable flight capabilities. Recent studies suggest that grey-headed albatrosses may be the fastest and most energy-efficient of the albatross species, yet no attempts have been made to replicate their wing design. A key factor in aircraft design is the airfoil, which remains uncharacterized for the grey-headed albatross. Other critical aspects, such as wing twist and dihedral/anhedral, also remain unquantified for any albatross species. This study aimed to fill this gap in the current knowledge by extracting detailed morphological data from a grey-headed albatross wing to recreate digitally. A well-preserved dried grey-headed albatross wing was scanned in the presence of airflow in a wind tunnel, at conditions that represent a grey-headed albatross in gliding flight. Wing cross-sections were extracted and smoothed to produce a series of airfoils along the wing span. The 3D properties such as wing dihedral/anhedral, sweep and twist were also extracted and used to build a CAD model of the wing. Variations in airfoil shape were observed along the wing span, with thicker, more cambered airfoils near the wing base. The model wing's camber was slightly higher, particularly in the arm section, but overall matched flight photographs. The body, tail, and bill were modelled based on available photographs and known dimensions from literature and merged with the wing to form the final bill-body-wing-tail model. This model is based on real grey-headed albatross morphology under aerodynamic pressure, in gliding flight. Although geometric changes due to scanner interference remain a limitation of this method, the extracted geometric data still provide valuable insights into wing performance under varying conditions. The geometry can also be fully parameterized for complex simulations, aiding studies of grey-headed albatross aerodynamics and engineering design, such as in aircraft or wind turbines at similar Reynolds numbers.

Development of a Reduced Order Model-Based Workflow for Integrating Computer-Aided Design Editors with Aerodynamics in a Virtual Reality Dashboard: Open Parametric Aircraft Model-1 Testcase

In this paper, a workflow for creating advanced aerodynamics design dashboards is proposed. A CAD modeler is directly linked to the CFD simulation results so that the designer can explore in real time, assisted by virtual reality (VR), how shape parameters affect the aerodynamics and choose the optimal combination to optimize performance. In this way, the time required for the conception of a new component can be drastically reduced because, even at the preliminary stage, the designer has all the necessary information to make more thoughtful choices. Thus, this work sets a highly ambitious and innovative goal: to create a smart design dashboard where every shape parameter is directly and in real-time linked to the results of the high-fidelity analyses. The OPAM (Open Parametric Aircraft Model), a simplified model of the Boeing 787, was considered as a case study. CAD parameterization and mesh morphing were combined to generate the design points (DPs), while Reduced Order Models (ROMs) were developed to link the results of the CFD analyses to the chosen parameterization. The ROMs were exported as FMUs (Functional Mockup Units) to be easily managed in any environment. Finally, a VR design dashboard was created in the Unity environment, enabling the interaction with the geometric model in order to observe in a fully immersive and intuitive environment how each shape parameter affects the physics involved. The MetaQuest 3 headset has been selected for these tests. Thus, the use of VR for a design platform represents another innovative aspect of this work.

STNeRF: symmetric triplane neural radiance fields for novel view synthesis from single-view vehicle images

This paper presents STNeRF, a method for synthesizing novel views of vehicles from single-view 2D images without the need for 3D ground truth data, such as point clouds, depth maps, CAD models, etc., as prior knowledge. A significant challenge in this task arises from the characteristics of CNNs and the utilization of local features can lead to a flattened representation of the synthesized image when training and validation with images from a single viewpoint. Many current methodologies tend to overlook local features and rely on global features throughout the entire reconstruction process, potentially resulting in the loss of fine-grained details in the synthesized image. To tackle this issue, we introduce Symmetric Triplane Neural Radiance Fields (STNeRF). STNeRF employs a triplane feature extractor with spatially aware convolution to extend 2D image features into 3D. This decouples the appearance component, which includes local features, and the shape component, which consists of global features, and utilizes them to construct a neural radiance field. These neural priors are then employed for rendering novel views. Furthermore, STNeRF leverages the symmetric properties of vehicles to liberate the appearance component from reliance on the original viewpoint and to align it with the symmetry of the target space, thereby enhancing the neural radiance field network’s ability to represent the invisible regions. The qualitative and quantitative evaluations demonstrate that STNeRF outperforms existing solutions in terms of both geometry and appearance reconstruction. More supplementary materials and the implementation code are available for access at the following link: https://github.com/ll594282475/STNeRF.

Design and mechanical analysis of bushings made from TPU using additive manufacturing and the finite element method

The study focused on analyzing the mechanical behavior of a front suspension fork bushing for an all-terrain vehicle (ATV), manufactured using Thermoplastic Polyurethane (TPU) through additive manufacturing, specifically 3D printing. This technology enables the creation of customized designs, reduces production time, and minimizes material waste. TPU, an elastomer with remarkable physical and mechanical properties, was evaluated as a potential substitute for natural rubber, which is the primary material traditionally used for bushings in the automotive industry, especially in the production of tires, hoses, and seals. The analysis was conducted through CAD modeling and finite element simulations, subjecting the bushing to torsional and shear stresses typical of vehicular suspension systems. The results indicated that TPU could serve as a replacement material for the established requirements. Given that replacement parts are not always acquired in a timely manner, the study focuses on providing a viable alternative for the automotive industry.

COMPARISON OF 3D-PRINTED PARTS’ QUALITY USING PRINTERS WITH “COREXY” AND “DELTA” KINEMATICS

Additive manufacturing, or 3D printing, describes technologies that manufacture parts by depositing thin layers of molten material on top of each other and creating the final part layer by layer. Each layer is built on the basis of geometry designed in CAD systems. Additive manufacturing technology opens up new design approaches: "design manufacturing" versus the traditional "design for manufacturing" approach. Geometric freedom allows you to design products as they are visualized, without manufacturing restrictions. Recently, 3D printers with Delta-type kinematics have gained popularity, which is an alternative to standard, cartesian 3D printers. These models use a more complex control system due to differences in the generation of print paths, but may have some advantages over a cartesian configuration. In order to expand the knowledge of additive manufacturing, a comparative study was conducted with cartesian and Delta printers to evaluate the printing performance of the test part. This article examines 3D printers with CoreXY and Delta kinematics, compares their characteristics, and identifies key differences in printing processes. As an example, for quality comparison, arbitrary parts printed in batches of three units from the same material with the same settings inside the slicer program were considered. Parts from both 3D printers were scanned using a LIDAR scanner, and the resulting scan models were transferred to a CAD environment for comparison. The results of the comparison were obtained by the shape and quality of the surface, the production time of one part and batch of parts, mass and dimensional characteristics. Looking at the results, it can be seen that the parts printed by the 3D printer with Delta kinematics have a better surface quality without post-processing, while the parts printed by the 3D printer with kinematics CoreXY correspond as closely as possible to the dimensions specified in the CAD model.

Transport Process of Virus Concentration from Airway to Cerebral Artery by using Computational Fluid Dynamics

When a person infected with the virus releases aerosol including the virus by sneezing or talking, the virus stays in atmosphere for a long time. If other persons inhale the virus, the person maybe infected. In our previous researches, in order to decrease efficiently the risk of infection, various indoor ventilation conditions have been evaluated by analyzing transport process of the virus concentration using Computational Fluid Dynamics (CFD). From them, it was found that indoor ventilation condition can be optimised by evaluating amount of the virus concentration and residence time. However, the infection process in air way and vascular when these airborne viruses from indoor air is inhaled has not been elucidated yet. In this research, a couple analysis from nasal cavity to cerebral artery via organ is tried to be applied in order to analyze the transport process of virus concentration from nasal cavity to cerebral artery. In addition, the effect of breathing waveforms and virus proliferation on the virus infection is evaluated. Regarding the methods, 3D CAD model of these three parts is created. Continuity equation, Navier-Stokes equation and transport equations of virus concentration are used as the governing equations. The transport equations in the organ is modified with the virus proliferation. Inlet boundary conditions in the nasal cavity are set up to be four types of breathing waveforms. A boundary condition between the nasal cavity and the organ is continuity of virus concentration at the contact surface. Similarly, the other boundary condition between the organ and the cerebral artery is continuity of virus concentration. As results, it was found that the virus concentration in the cerebral artery in case of sinusoidal breathing waveform with long period is the smallest. It was also found that the virus concentration in the organ and the cerebral artery in case of proliferation within the organ is higher than that has no proliferations. It is concluded that a method for minimalizing risk of virus infection can be proposed by the couple analysis.

Optimisation of process parameters in Arburg Plastic Freeforming for enhanced part density and geometric accuracy

Technological advances have increased the use of plastic-based additive manufacturing for production in a variety of industries that require high mechanical properties while maintaining geometric precision. The Arburg Plastic Freeformer (APF) process, unlike other filament-based technologies, uses standard plastic granules used in mass production in injection moulding machines. This study focuses on optimising the interaction of three critical process parameters: layer thickness (LT), droplet aspect ratio (DAR) and discharge rate (DR). Previous studies have mainly varied individual parameters to evaluate mechanical and geometrical properties. In contrast, this work analyses these parameters as a whole and evaluates their combined effects on residual porosity and geometric accuracy. APF relies heavily on supports to sustain the printed part, with a smaller achievable self-supporting overhang angle compared to the Fused Filament Fabrication (FFF) printing process. For this reason, this study investigates two compatible materials, ABS Terluran GP35 and a water-soluble PVP compound named Armat11. Cylindrical and cubic samples were 3D printed using different combinations of LT, DAR and DR. A total of 150 cubic samples were printed to assess the geometric dimensional accuracy and repeatability of printing in the plate position using permutations in the printing plate. Subsequently, 30 cylindrical samples were printed for micro-CT analysis, reconstructed by CT file segmentation and compared with the ideal CAD model, in addition to the characterisation of residual porosity. The results show that optimal combinations of LT, DAR and DR produce high density parts with repeatable geometric properties. In addition, a quantitative analytical model was developed to optimise arbitrary parameter sets. This comprehensive investigation provides important insights into the APF process and increases its potential for wider industrial applications.

The Accuracy of 3D-Printed Fixed Dental Restorations.

The aim of this invitro study was to evaluate the accuracy of resin-based fixed dental restorations, namely veneers, single crowns, and four-unit fixed partial dental prosthesis (FPDs), using two different 3D printing technologies and polymer-based materials. A standard maxillary polyurethane jaw model containing prepared teeth was scanned using an intraoral scanner. The generated STL data were used to design the restorations virtually using CAD software. Two 3D printers were utilized for the provisional digital light processing and stereolithography for the castable resin patterns. Each printer produced 10 specimens of each type of restoration, for a total of 80 restorations. The 3D-printed restorations were then 3D scanned using the same intraoral scanner and evaluated for external and internal dimensional accuracy in terms of trueness and precision. A one-way ANOVA and two-sample T-test were implemented to compute the precision (variability between groups) and trueness (with the designed CAD model). A level of statistical significance of p-value < 0.05 was set. Statistical differences in the external dimensional analysis of the incisors, molars, and four-unit FPD with p-values < 0.001, 0.002, and 0.004, respectively. For the internal dimensional analysis, the overall mean values of trueness ranged between 17 and 52 μm, and the variability was significant. The external and internal dimensional accuracy values of the 3D-printed fixed dental restorations in this invitro study in terms of trueness can be clinically accepted after chairside modifications. However, significant variability between the 3D-printed restorations was observed. Further investigations are needed to improve the accuracy of the 3D-printed fixed dental restorations. In terms of clinical applications, 3D-printed fixed dental restorations produced by both 3D-printing technologies and polymer-based materials achieved acceptable levels of trueness, although some variability was observed. Significant deviations from the CAD model may require further chairside adjustments. Future integration of AI with 3D-printing may further improve the accuracy and efficiency of fixed dental restoration production.

Multipath Projection Stereolithography for Three-Dimensional Printing Microfluidic Devices.

Although many lab-on-chip applications require inch-sized devices with microscale feature resolution, achieving this via current 3D printing methods remains challenging due to inherent trade-offs between print resolution, design complexity, and build sizes. Inspired by microscopes that can switch objectives to achieve multiscale imaging, we report a new optical printer coined multipath projection stereolithography (MPS) specifically designed for printing microfluidic devices. MPS is designed to switch between high-resolution (1× mode, ∼10 μm) and low-resolution (3× mode, ∼30 μm) optical paths to generate centimeter-sized constructs (3 × 6 cm) with a feature resolution of ∼10 μm. Illumination and projection systems were designed, resin formulations were optimized, and slicing software was integrated with hardware with the goal of ease of use. Using a test case of micromixers, we show that user-defined CAD models can be directly input to an automated slicing software to define printing of low-resolution features via the 3× mode with embedded microscale fins via 1× mode. A new computational model, validated using experimental results, was used to simulate various fin designs, and experiments were conducted to verify simulated mixing efficiencies. New 3D out-of-plane micromixer designs were simulated and tested. To show broad applications of MPS, multichambered chips and microfluidic devices with microtraps were also printed. Overall, MPS can be a new fabrication tool to rapidly print a range of lab-on-chip applications.

Prototype of Laboratory Scale Centrifuge for Gum Crude Palm Oil (CPO) Separate

This study concentrates on the design and construction of a laboratory-scale centrifuge for the separation of gum from crude palm oil (CPO). The extraction of gum from CPO is essential in the palm oil sector to guarantee that the finished product adheres to quality standards and is safe for consumption. We engineered the prototype centrifuge to accommodate six 600-mL bottles and achieve a maximum rotational speed of 1400 rpm. The design procedure utilised Autodesk Inventor software for CAD modelling and computations to ascertain the centrifugal force, power capacity, and shaft diameter. The process of manufacturing entailed cutting and shaping stainless steel into the necessary components, subsequently followed by drilling and milling operations for mounting points and interfaces. We implemented surface treatment to augment corrosion resistance and elevate visual appeal. The assembling procedure encompassed component integration, motor incorporation, and control system configuration. The experimental configuration involved centrifugal testing utilising 600-mL glass bottles with time intervals of 10, 20, 30, and 40 minutes at an average rotational speed of 924 rpm. The experiment showed that the centrifuge worked well to separate the gum and other contaminants from the CPO. The best separation happened after 40 minutes of centrifugation.

Numerical modelling of a soil structure interaction for a torpedo base conductor in a petroleum well under an extreme lateral load

This work aims to compare the performance, regarding the soil structure interaction, of a torpedo base conductor and a jetted conductor, considering a drilling rig drift-off scenario. This can be considered an extreme load scenario and the results will be shown for lateral loads coming from the interaction between the wellhead and the drilling rig, drilling riser and BOP.A complete 3D CAD model of the Torpedo Base Conductor was created and the soil was also modelled with 3D elements. Based on previous references, the selected 3D soil element was the Drucker-Prager constitutive model (Costa, 2008, Aysen, 2016 and Sanomia, 2016). Notably, the Drucker-Prager model accounts for non-homogeneous soil, meaning that the material properties vary with depth according to its undrained shear strength profile.The final results show the behavior of soil under lateral loads for both the torpedo base and the jetted conductor, as well as the structural response. The final conclusion is that the torpedo base has a better performance under lateral loads than the jetted conductor and can be considered a good well foundation solution to mitigate problems associated with interventions with dynamic position drilling rigs in shallower water depth.

Model-based dimensional NDE from few X-ray radiographs: Application to the evaluation of wall thickness in metallic turbine blades

The extraction of 3D dimensional measurements based on a limited number of 2D X-ray radiographs of a part would offer a significant speed-up of quality control procedures in industry. However, there are challenges with respect to both measurements and uncertainties. This work addresses these challenges by creating an estimated numerical model of the imaged part on which dimensional measurements can be made. The numerical model is chosen as a parametric deformable model that encodes the expected shape variability of the parts resulting from the manufacturing process. The parameters and uncertainties of the numerical model of the imaged part are estimated by the registration of the computed projections of the model and the observed radiographs without the need of any segmentation. The registration requires the model, the initial parameters, and the observed radiographs. The proposed approach is applied to the inspection of turbine blades manufactured by investment casting, and in particular to the measurement of their wall thickness, which is a critical control. The deformable model consists in partitioning the inner ceramic core into multiple subparts, which may undergo a rigid body motion with respect to the master die. Wall thickness measurements are determined from the estimation of these rigid body motions. To assess the reliability of the proposed procedure, a repeatability study is performed. In addition, wall thickness measurements were compared to corresponding measurements from the surface of the metal boundary obtained by X-ray computed tomography. This surface was determined from a reconstructed tomogram using commercial software. Both analyses show that such measurements are reliable and efficient. Furthermore, residual differences between captured and computed projections reveal localized shape deviations from the CAD model, meaning that despite localized model errors, the approach is operable.

Adaptive Spline Surface Fitting With Arbitrary Topological Control Mesh.

Reconstructing a spline surface from a given arbitrary topological triangle mesh is a fundamental and challenging problem in computer-aided design and engineering. This article introduces a novel surface fitting method utilizing G-NURBS capable of handling control meshes with arbitrary topologies. This method employs adaptive control point adjustment, guided by the geometric attributes of the input model, ensuring precise representation of sharp features such as edges and corners. Two primary strategies are employed: A parameter correspondence approach designed for sharp features and a control mesh iterative refinement technique that incorporates geometrical feature information. The proposed method has been tested and evaluated on various CAD models to demonstrate its effectiveness. This method can achieve higher fitting accuracy while faithfully preserving the geometrical features with fewer control points.

CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation.

Object pose estimation constitutes a critical area within the domain of 3D vision. While contemporary state-of-the-art methods that leverage real-world pose annotations have demonstrated commendable performance, the procurement of such real training data incurs substantial costs. This paper focuses on a specific setting wherein only 3D CAD models are utilized as a priori knowledge, devoid of any background or clutter information. We introduce a novel method, CPPF++, designed for sim-to-real category-level pose estimation. This method builds upon the foundational point-pair voting scheme of CPPF, reformulating it through a probabilistic view. To address the challenge posed by vote collision, we propose a novel approach that involves modeling the voting uncertainty by estimating the probabilistic distribution of each point pair within the canonical space. Furthermore, we augment the contextual information provided by each voting unit through the introduction of N-point tuples. To enhance the robustness and accuracy of the model, we incorporate several innovative modules, including noisy pair filtering, online alignment optimization, and a tuple feature ensemble. Alongside these methodological advancements, we introduce a new category-level pose estimation dataset, named DiversePose 300. Empirical evidence demonstrates that our method significantly surpasses previous sim-to-real approaches and achieves comparable or superior performance on novel datasets.

A comprehensive RGB-D dataset for 6D pose estimation for industrial robots pick and place: Creation and real-world validation

In the field of robotic grasping, 2D pose estimation algorithms are outdated and insufficient for modern requirements. Transitioning to 6D pose estimation of objects offers, particularly through deep learning methods, significantly improved performance. However, most high-performance 6D algorithms lack publicly disclosed methods for creating the necessary datasets, presenting challenges for researchers. This study introduces a methodology for creating a sample dataset for 6D pose estimation, addressing the challenges researchers face when applying these algorithms to specific projects. RGB and depth images are captured using Intel® RealSense™ Depth D435 camera, forming the foundation for accurately determining the pose of each object in the dataset. A CAD model along with accompanying metadata files, is generated to provide a complete dataset. The sample dataset was tested on two algorithms: EfficientPose and FFB6D, achieving accuracy rates of 97.05 % and 98.09 % respectively. These results indicate that the dataset is both effective and applicable to real-world robotic grasping tasks. Our research offers substantial practical value, enabling researchers and engineers to easily apply state-of-the-art 6D pose estimation algorithms to fields such as conveyor belt robotic picking, medical automation, and various other applications.

Creating Digital Twin of the Cheese Production Line Using Virtual Reality Technology

The main stages of the project life cycle are considered, its schedule is presented in the form of a Gantt chart. A method for designing the line using virtual reality technology is proposed which includes four stages: designing a 3D CAD model, importing a model, creating a scene, testing the system. To evaluate the approach, a user survey was conducted which proves the need to use a digital twin for designing the cheese production line.

Conforming embedded isogeometric analysis for B-Rep CAD models with strong imposition of Dirichlet boundary conditions using trivariate B++ splines

Strong imposition of Dirichlet boundary conditions for immersed finite element methods or immersed isogeometric methods remains a challenge. To address this issue, this paper presents a 3D conforming embedded isogeometric method for Boundary-Represented (B-Rep) solid CAD models by generalizing our bivariate B++ splines to trivariate B++ Splines. The proposed method can convert a B-Rep model into a trivariate B++ spline solid patch with body-fitted boundary representation while retaining key features of B-rep models, such as sharp points, sharp edges, and holes. The basis functions of the trivariate B++ spline solid patch satisfy the Kronecker delta property, which implies that we can strongly impose Dirichlet boundary conditions on B-Rep models without the necessity of Nitsche's method. The presented method can be viewed as a parameterization method that inherits the advantages of volumetric parameterization methods in that the basis functions of a reconstructed geometry satisfy the Galerkin method. In addition, compared with T-splines, the proposed method does not generate the extraordinary point and can achieve optimal convergence rate. Several numerical examples are used to demonstrate the reliability of the presented method.

Simulating and Verifying a 2D/3D Laser Line Sensor Measurement Algorithm on CAD Models and Real Objects.

The increasing adoption of 2D/3D laser line sensors in industrial and research applications necessitates accurate and efficient simulation tools for tasks such as surface inspection, dimensional verification, and quality control. This paper presents a novel algorithm developed in MATLAB for simulating the measurements of any 2D/3D laser line sensor on STL CAD models. The algorithm uses a modified fast-ray triangular intersection method, addressing challenges such as overlapping triangles in assembly models and incorporating sensor resolution to ensure realistic simulations. Quantitative analysis shows a significant reduction in computation time, enhancing the practical utility of the algorithm. The simulation results exhibit a mean deviation of 0.42 mm when compared to real-world measurements. Notably, the algorithm effectively handles complex geometric features, such as holes and grooves, and offers flexibility in generating point cloud data in both local and global coordinate systems. This work not only reduces the need for physical prototyping, thereby contributing to sustainability, but also supports AI training by generating accurate synthetic data. Future work should aim to further optimize the simulation speed and explore noise modeling to enhance the realism of simulated measurements.

A Digital Twin-based paradigm for programming and control of cooperating robots in reconfigurable production systems

ABSTRACT The shift towards product personalization is the main enabler behind Industry 4.0 and drives the need to deploy flexible and reconfigurable assembly systems. This paper investigates the use of Digital Twins (DT) for enabling system flexibility and reconfigurability through various functionalities, leading to an overall resilience in the system. The suggested DT infrastructure involves two main components: a) Virtual representation of the shop floor, combining multiple sensor data and CAD models and b) Real-time multi-robot behaviour control. The communication layer between the physical and the virtual agents in the level of Digital Twin is realised through the ROS framework. The integration of the DT in an overall production system with various components (like planning systems) is realised through the Asset Administration Shell (AAS) and custom ROS-AAS connectors responsible for translating data between the two formats. Finally, an orchestration system (referred as Station Controller) that is responsible for dispatching planned tasks to the assigned resources has been implemented. The developed infrastructure is validated through a case study inspired by the consumer electronics industry focusing on the assembly of two different products, a trimmer head, and a monitor cover. Nevertheless, the proposed solution has been designed to be easily applicable to any similar scenario.

Implementation of additive 3D printing technology in the development of an experimental oxygen-hydrogen low thrust rocket engine

The creation of spacecraft propulsion systems with high energy efficiency and minimal weight and size parameters is an urgent scientific and technical task of the domestic rocket engine industry. At the same time, requirements are put forward to optimize the cost and time of design, development and manufacturing of engines, as well as environmental safety at all stages of the product life cycle. In this regard, it is proposed to use advanced laser 3D printing technologies (additive technologies) from metal powder using CAD models of engine parts in the production of space low thrust rocket engines (LTRE). Laser melting technology on modern 3D printers makes it possible to produce complex monolithic engine structures without the use of labor-intensive and resource-intensive operations of machining, welding, and soldering, as well as a significant reduction in the volume of plumbing, assembly, control and measuring work, and a decrease in the influence of some non-production factors. The article discusses issues of practical application of promising technologies in the creation of LTRE. The results of fire tests are presented, which will be used to refine the previously developed calculation models of oxygen-hydrogen LTRE when creating advanced rocket engines for spacecraft. The object of the study was an experimental sample of LTRE with a nominal thrust of 150 N using gaseous fuel components oxygen and hydrogen, developed and manufactured using additive technology. The experimental LTRE is considered as a prototype of the engine for orientation, stabilization and launching of the oxygen-hydrogen upper stage. The purpose of the work is to study the effectiveness of previously unexplored design solutions for organizing mixture formation and cooling of an oxygen-hydrogen LTRE, to determine their influence on the perfection of the working process and the thermal state of the engine chamber. Fire tests were carried out in single switching mode with a duration sufficient for the LTRE chamber to reach a stationary thermal regime, with the determination of the energy characteristics and thermal state of the structure.