Computer-aided Engineering Research Articles

Static Loading Simulation on Temporary Platform and Ladder Absorbent Chamber Design

This study utilizes SolidWorks software to thoroughly examine the structural layout and static load simulation of a temporary platform and ladder in an adsorbent chamber. SolidWorks, a computer-aided design (CAD) and computer-aided engineering (CAE) software, offers robust tools for 3D modeling, simulation, and analysis, making it ideal for this type of structural assessment. Finite element analysis (FEA), a simulation model within SolidWorks, is employed to determine stress distribution and safety factors. The results demonstrate the platform's maximum stress at 198.65 MPa, below the yield strength of ASTM A36 Steel, leading to a safety factor of 1.3. These findings validate the design's safety and reliability for industrial use.

Implementation of CAD/CAM/CAE Systems for Improved Design and Manufacturing Processes in Industrial Organizations

Abstract The industrial sector rapidly integrates CAD (computer-aided design), CAE (computer-aided engineering) and CAM (computer-aided manufacturing) systems that have changed how firms advance their design and manufacturing processes. Imagine technology spreading like wildfire—this is what our latest study maps out. It details the perks these innovations bring along and weighs them against the hiccups experienced in age-old setups. Highlighted within our findings are impressive improvements concerning efficiency and reliability which boost productivity immensely—if correctly adjusted for optimal use. Specifically, through an extensive literature review it examines application of CAD/CAM/CAE systems within various industrial settings. Better operational results are definitely on the horizon with this strategy. Imagine cutting down on time without sacrificing quality; this is exactly what recent developments contribute to our project workflows—enhanced productivity coupled with pinpoint accuracy. Reviewing case studies across various sectors shows how successfully technology upgrades have been embraced during industrialization. The learning curve may be steep but costs can be recovered quickly if properly managed is the key inference from examining these examples.

Generalized functionals for qualification of geological carbon storage injection sites

Many nations have pledged to reach carbon neutrality by 2050. Embarking on the decarbonization journey, they posited geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework. The CCUS chain operates to reduce “hard-to-abate” emissions at key sectors by capturing carbon dioxide (CO2), reusing it, transporting it, or disposing of it via injection into underground geological formations for permanent storage. Despite the global success of GCS ventures, mainly driven by the oil and gas industry, GCS initiatives are still in their early stages in several developing countries. In Brazil, for instance, a full setup covering precise storage capacity databases, potential CCUS clusters, national regulatory structure, and auxiliary computer-aided engineering is underway. Intended to push the frontier in the latter subject, this paper introduces mathematical models for qualifying underground CO2 storage sites. Our research explores a family of multivariate functionals endowed with underlying reservoir features and distinct weighting functions, thus envisioning two primary objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions considering structural traps/caprocks settings. Backed by the Matlab Reservoir Simulation Toolbox (MRST) capabilities, the methodology is a subsidiary resource for identifying suitable injection and storage sites. A case study using the UNISIM-I-D model generated dozens of volumetric quality maps that point to unique potential storage sites. Numerical simulation experiments of injection comparing legacy and novel wells reveal storage surpluses improved by up to 50%. The paper seeks to establish foundational knowledge in GCS efficiency for general underground settings. One expects that these outcomes leverage well-repurposing perspectives and stimulate field appraisal actions to scale up GCS projects both in Brazil and worldwide.

Computational design of myoglobin-based carbene transferases for monoterpene derivatization

Carbene transfer reactions have emerged as pivotal methodologies for the synthesis of complex molecular architectures. Heme protein-catalyzed carbene transfer reactions have shown promising results on model compounds. However, their limited substrate scope has hindered their application in natural product functionalization. Building upon the foundation of previously published work on a carbene transferase-myoglobin variant, this study employs computer-aided protein engineering to design myoglobin variants, using either docking or the deep learning-based LigandMPNN method. These variants were utilized as catalysts in carbene transfer reactions with a selection of monoterpene substrates featuring C–C double bonds, leading to seven target products. This cost-effective methodology broadens the substrate scope for heme protein-catalyzed reactions, thereby opening novel pathways for research in heme protein functionalities and offering fresh perspectives in the synthesis of bioactive molecules.

Development and evaluation of RFID-integrated endoscopic clips for laparoscopic surgery marking.

As advancements in surgical instruments and techniques continue to evolve, minimally invasive surgery has become increasingly preferred as a means of reducing patient pain and recovery time. However, one major challenge in performing minimally invasive surgery for early gastrointestinal cancer is accurately identifying the location of the lesion. This is particularly difficult when the lesion is confined to the lumen of the intestine and cannot be visually confirmed from the outside during surgery. In such cases, surgeons must rely on CT or endoscopic imaging to locate the lesion. However, if the lesion is difficult to identify with these images or if the surgeon has less experience, it can be challenging to determine its precise location. This can result in an excessive resection margin, deviating from the goal of minimally invasive surgery. To address this challenge, researchers have been studying the development of a marker for identifying the lesion using a radio-frequency identification (RFID) system. One proposed method for clinical application of this detection system is to attach an RFID tag to an endoscopic hemostatic clip and fix it to the intended position, providing a stable marker for the inner wall of the organ. This approach has the potential to improve the accuracy and effectiveness of minimally invasive surgery for early gastrointestinal cancer. In the development of a marker for identifying gastrointestinal lesions using a radio-frequency identification (RFID) system, the shape of the clip and suitable materials for attaching the RFID tag were determined through finite element method (FEM) analysis. A prototype of the clip was then fabricated and ex-vivo experiments were conducted using porcine intestine to evaluate the stability of the clip in relation to its position. To further evaluate the performance of the RFID-integrated clip in vivo, the clip was placed in the gastric wall of the stomach of anesthetized porcine using an endoscopic instrument. The clip was then detected using a RFID detector designed for laparoscopic approach. And later, the accuracy of detection was confirmed by incising the lesion. The design and fabrication of a clip with varying thicknesses using STS316 and STS304 stainless steel were accomplished using the results of finite element method analysis. The stability of the clip was evaluated through ex-vivo experiments, showing it to be a viable option. In-vivo experiments were performed on anesthetized porcine, in which the RFID-integrated clip was placed in the gastric wall and detected using a custom-made RFID detector. The resection margin, measured at about 30 mm from the detector position, was accomplished with low error. These findings indicate the feasibility and efficacy of using an RFID-integrated clip as a marker in minimally invasive surgery for the identification of gastrointestinal lesions. The study evaluated the feasibility of using stainless steel clips for lesion detection in endoscopic surgery using computer-aided engineering analysis and ex-vivo experimentation. Results showed that STS304 was suitable for use while STS316L was not. The ex-vivo experiments revealed that the clip holding force and tissue retention length varied depending on the location of attachment. In-vivo experiments confirmed the accuracy and usefulness of the RFID lesion detection system. However, challenges remain for its use in clinical field, such as ensuring the stability of the clip and the safe attachment of the RFID tag, which requires further research for commercialization.

Computational Fluid Dynamics (CFD) Analysis of Bioprinting.

Regenerative medicine has evolved with the rise of tissue engineering due to advancements in healthcare and technology. In recent years, bioprinting has been an upcoming approach to traditional tissue engineering practices, through the fabrication of functional tissue by its layer-by-layer deposition process. This overcomes challenges such as irregular cell distribution and limited cell density, and it can potentially address organ shortages, increasing transplant options. Bioprinting fully functional organs is a long stretch but the advancement is rapidly growing due to its precision and compatibility with complex geometries. Computational Fluid Dynamics (CFD), a carestone of computer-aided engineering, has been instrumental in assisting bioprinting research and development by cutting costs and saving time. CFD optimizes bioprinting by testing parameters such as shear stress, diffusivity, and cell viability, reducing repetitive experiments and aiding in material selection and bioprinter nozzle design. This review discusses the current application of CFD in bioprinting and its potential to enhance the technology that can contribute to the evolution of regenerative medicine.

Analysis of the Effect of Feeder Volume on Shrinkage Porosity Defects in Piston Products through the Gravity Die Casting Process

To achieve defect-free casting (soundness casting) with a minimal amount of shrinkage porosity, refinement during the casting process is necessary. In the gravity die casting process, there are parameters that lead to product defects, especially in the casting design, focusing on the gating system and feeder system as pathways for the flow of molten metal to supply the molten metal into the mold cavity. This research was conducted to examine the effect of adding feeder dimensions on shrinkage porosity, specifically on Al-Si piston products with a Silicon content of 12-13%. Feeder dimensions were varied in nine variations by adding height and width to the feeder gate, initially measuring 90mm in height and 32mm in width, along with the addition of insulation to the feeder to retain the heat of the casting process. Cooling used water and argon, with water placed at the center core and pin core and argon placed on the outer mold, with a solidification time of 150 seconds and pouring time of 3 seconds considered constant. This study used a Computer Aided Engineering (CAE) approach, namely MagmaSoft or the application of software to model the gravity casting system process. The results showed the lowest percentage of shrinkage at feeder dimensions of 114mm in height and 45mm in width with a mold temperature of 220°C was 0.76% of the product

Fostering Design for Sustainability through the Adoption of Computer-Aided Engineering Tools in the Development of Energy-Related Products

The main challenge to face in the development of energy-related products is represented by the adoption of effective design for sustainability strategies that encompasses the adoption of engineering design tools, knowledge collection, and reuse/sharing in technical departments. This present paper proposes an engineering design for sustainability methodology that assists engineers in developing energy-related products in compliance with ecodesign standards. The methodology uses virtual prototyping tools to assess energy consumption in compliance with energy labeling directives and analyze different use scenarios. The results obtained by numerical simulations (e.g., Finite Element Method—FEM, Computational Fluid Dynamics—CFD) are used to create specific design eco-knowledge in the field of energy-related products. Numerical results are linked with design configurations to understand the benefits introduced by engineering design choices. This knowledge is stored in a structured database with the aim of being reused when a new product is developed or improved/upgraded. The case study of an induction hob, belonging to the household appliance product family, is investigated to understand the potential and drawbacks of the presented approach in a real application. The results show that potential energy and environmental performance benefits are achieved (e.g., reduction of energy losses, achievement of A+ energy class, and overall life cycle environmental impact reduction). Additionally, a new set of ecodesign guidelines are defined for this product family and employed in developing new compliant products belonging to the same family.

Computational assessment of carbon fabric reinforced polymer made prosthetic knee: Mechanics, finite element simulations and experimental evaluation.

A prosthetic knee is designed to replace the functionality of an anatomical knee in transfemoral amputees. The purpose of a prosthetic knee is to restore mobility and compensate amputees for their impairment. In the present research numerical modelling and simulation of a carbon fabric reinforced polymer made polycentric prosthetic knee with four-bar mechanism was performed. Virtual prototyping with computer-aided design and computer-aided engineering software ensured geometric and structural stability of the knee design. The linkage mechanism, instantaneous centre's location and trajectory were investigated using multibody dynamics and analytical formulations. Computational simulations with a non-linear finite element model were employed with joints, contact formulations and an orthotropic material model to predict the displacement, stress formulated and life of the knee prosthesis under static and cyclic loading conditions. Finite element analysis assessed the strength and durability of knee in accordance to standards. Maximum Principal stress of 155 MPa and life expectancy of 3.1 × 106 cycles were determined for the composite knee through numerical simulations ensuring a safe design. Experimental testing was also conducted as per standards and the percentage error was estimated to be 2.52%, thereby establishing the validity of the finite element model deployed. This type of simulation-based approach can be implemented to efficiently and affordably design and prototype a prosthetic knee with desired functioning criteria.

A hybrid CAD/CAE/CAM project‐based laboratory framework integrating topology optimization and laser powder bed fusion for engineering education

AbstractIn the era of Industry 4.0, laser‐based additive manufacturing (LBAM) has gained substantial momentum in the production of complex lightweight structures in several domains such as aerospace, civil, and biomedical engineering. The increasing demand for consistent and precise manufacturing processes has urged the manufacturing industry to consider the coupling of topology optimization (TO) and laser powder bed fusion (LPBF) in the design of sophisticatedly novel topologies that are unattainable through traditional processes. Notably, this union has demonstrated a highly efficient and productive capability toward the manufacturing industry. In line with this accelerated pace, engineering programs within universities exert significant effort to revise and update their engineering curriculum design to incorporate emerging manufacturing technologies providing students with skills that are aligned with the actual industrial context. In this article, a computer‐aided design (CAD)/computer‐aided engineering (CAE)/computer‐aided manufacturing (CAM) project‐based laboratory framework is proposed combining TO and LPBF exploiting a simulation‐based environment integrating CAD, CAE, and CAM. The structure of the proposed CAD/CAE/CAM design methodology is revisited to discern the added value of the newly developed framework and its particularity in assisting aerospace engineering students to meet industrial expectations. A new CAD/CAE/CAM project‐based laboratory framework has been developed integrating TO and LPBF using advanced engineering tools within the aerospace engineering education.

An Enhanced Temperature Control Approach to Simulate Profile Extrusion.

Thermoplastic extrusion, a widely used method for processing thermoplastic materials, requires precise temperature control to ensure product quality. However, existing computer-aided engineering tools often oversimplify the temperature distribution calculations, leading to additional discrepancies between simulations and the actual processes. This study introduces a novel multi-region modeling approach to address this issue. By employing realistic temperature control conditions, the methodology overcomes the limitations of current numerical modeling tools. The key contributions include the development of a transient, incompressible, non-isothermal solver integrated into the OpenFOAM computational library and the implementation of a specialized boundary condition that emulates Proportional-Integral-Derivative (PID) control using real-time thermocouple measurements. The findings highlight temperature deviations at the flow channel walls and total pressure drop while demonstrating a smaller impact on velocity and flow uniformity at the outlet under steady-state conditions. This research substantially advances the understanding of thermal dynamics in extrusion processes, offering crucial insights for enhancing temperature control and laying the groundwork for more effective and precise operational strategies.

A Review of Generative Models for 3D Vehicle Wheel Generation and Synthesis

Integrating deep learning methodologies is pivotal in shaping the continuous evolution of computer-aided design (CAD) and computer-aided engineering (CAE) systems. This review explores the integration of deep learning in CAD and CAE, particularly focusing on generative models for simulating 3D vehicle wheels. It highlights the challenges of traditional CAD/CAE, such as manual design and simulation limitations, and proposes deep learning, especially generative models, as a solution. The study aims to automate and enhance 3D vehicle wheel design, improve CAE simulations, predict mechanical characteristics, and optimize performance metrics. It employs deep learning architectures like variational autoencoders (VAEs), convolutional neural networks (CNNs), and generative adversarial networks (GANs) to learn from diverse 3D wheel designs and generate optimized solutions. The anticipated outcomes include more efficient design processes, improved simulation accuracy, and adaptable design solutions, facilitating the integration of deep learning models into existing CAD/CAE systems. This integration is expected to transform design and engineering practices by offering insights into the potential of these technologies.

Modelling of hybrid biocomposites for automotive structural applications

The demand for environmentally friendly materials is at its peak, and government legislations have become stricter and no longer tolerate violations. With biocomposites emerging as structural components instead of being hidden as non-structural applications and interiors, the automotive and motorsport sector started considering them for structural body parts. Natural fibres abundance, commercial availability, renewability, low density, low cost, and high tensile strength make biocomposite materials excellent candidates for eco-friendly vehicles. Several studies reported the utilisation of biocomposites as high-performance components and structural applications. However, current computer-aided engineering and modelling tools are insufficient to explore the vast field of possibilities during biocomposite materials selection to accurately predict the components' behaviour and analyses. Therefore, this study focuses on creating a material model to predict the behaviour of biocomposite materials. Additionally, the model is numerically implemented to illustrate the deformation and bending stiffness capabilities of a motorsport monocoque chassis structure application. A micromechanics modelling combining rate-dependant constitutive laws and multi-site interactions of inclusions is developed for studying the nonlinear response of composite materials. To avoid numerical instabilities when increments of time become very small, a regulation procedure concerning the visco-plastic function is adopted in the computation of the consistent tangent modulus. Based on the Generalised Mori–Tanaka (GMT) scheme, the effective properties are obtained for the nonlinear composite. The accuracy of the model is evaluated and validated by comparison results from the open literature. Finally, the developed constitutive equations are implemented as a user-defined material UMAT in a Finite Element code, leading to an application on a bio-based composite for the bamboo/flax fibre-reinforced epoxy hybrid composite materials.

Optimization of a tetrahedron compliant spherical joint via computer-aided engineering tools

This article focuses on enhancing the range of motion (ROM) of the Tetra II joint, a spherical compliant joint consisting of three internally interconnected tetrahedron-shaped elements that achieve motion through elastic deformation. Despite its excellent precision, this specific design is constrained in terms of ROM due to internal contacts among the tetrahedral elements. To overcome this limitation, this study utilizes a computer-aided engineering (CAE) framework to optimize the configuration of the Tetra II joint and enhance its ROM. The resultant optimized joint, referred to as Tetra III, is subsequently compared to Tetra II in terms of both ROM and center shift. Finite element models (FEM) are employed to validate the optimization results and examine how various tetrahedron-shaped geometries impact the joint’s performance. The newly optimized joint exhibits a significantly higher ROM compared to the previous version, while maintaining excellent precision and overall smaller dimensions. Finally, to demonstrate its manufacturability, the Tetra III joint is produced using selective laser sintering (SLS) technology, with Duraform PA serving as the construction material. The successful fabrication serves as a demonstrative example of the improved design of the Tetra III joint.

3D printing of personalised stents using new advanced photopolymerizable resins and Ti-6Al-4V alloy

PurposeThe development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.Design/methodology/approachThe methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.FindingsA series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.Originality/valueThis study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

Programmable and Modularized Gas Sensor Integrated by 3D Printing.

The rapid advancement of intelligent manufacturing technology has enabled electronic equipment to achieve synergistic design and programmable optimization through computer-aided engineering. Three-dimensional (3D) printing, with the unique characteristics of near-net-shape forming and mold-free fabrication, serves as an effective medium for the materialization of digital designs into usable devices. This methodology is particularly applicable to gas sensors, where performance can be collaboratively optimized by the tailored design of each internal module including composition, microstructure, and architecture. Meanwhile, diverse 3D printing technologies can realize modularized fabrication according to the application requirements. The integration of artificial intelligence software systems further facilitates the output of precise and dependable signals. Simultaneously, the self-learning capabilities of the system also promote programmable optimization for the hardware, fostering continuous improvement of gas sensors for dynamic environments. This review investigates the latest studies on 3D-printed gas sensor devices and relevant components, elucidating the technical features and advantages of different 3D printing processes. A general testing framework for the performance evaluation of customized gas sensors is proposed. Additionally, it highlights the superiority and challenges of programmable and modularized gas sensors, providing a comprehensive reference for material adjustments, structure design, and process modifications for advanced gas sensor devices.

Multi-patch parameterization method for isogeometric analysis using singular structure of cross-field

Isogeometric analysis is an innovative numerical paradigm with the potential to bridge the gap between Computer-Aided Design and Computer-Aided Engineering. However, constructing analysis-suitable parameterizations from a given boundary representation remains a critical challenge in the isogeometric design-through-analysis pipeline, particularly for computational domains with complex geometries, such as high-genus cases. To tackle this issue, we propose a multi-patch parameterization method for computational domains grounded in the singular structure of cross-fields. Initially, the vector field functions over the computational domain are solved using the boundary element method. The cross-field is then obtained through the one-to-one mapping between the vector field and the cross-field. Subsequently, we acquire the position information and topological connection relations of singularities and streamlines by analyzing the singular structure of the cross-field. Moreover, we introduce a simple and effective method for computing streamlines. We propose a novel segmentation strategy to divide the computational domain into several quadrilateral NURBS sub-patches. Once the multi-patch structure is established, we develop two methods to construct analysis-suitable multi-patch parameterizations. The first method is a direct generalization of the barrier function-based approach, while the second method yields smoother parameterizations by incorporating the interface control points of sub-patches into the optimization model. Numerical experiments demonstrate the effectiveness and robustness of the proposed method.

OPTIMAL DESIGN OF THE TRADITIONAL CHINESE WOOD FURNITURE JOINT BASED ON EXPERIMENTAL AND NUMERICAL METHODS

In this study, computer aided technology was utilized to improve the traditional grid shoulder mortise-and-tenon joint (GSMTJ). Firstly, the traditional GSMTJ was redesigned through using separated loose tenon by the computer aided design (CAD) software called AutoCAD. And then the mechanical strengths of the traditional GSMTJs and the improved GSMTJs were compared and analyzed using the experimentally validated finite element method (FEM) based on the computer aided engineering (CAE) software called ABAQUS. Finally, the GSMTJs were further investigated from perspective of manufacturing efficiency using the computer aided manufacturing (CAM) software called JDSoft SurfMill. Based on the above simulation analysis, the improved GSMTJ was validated to be equivalent strength, high manufacturing efficiency increasing by 11.5%, low processing load ratio decreasing by 30%, as well as less wood material cost reducing by 3.6% compared with the traditional GSMTJ. The proposed improved GSMTJ was validated to be more suitable to modern wood processing machines. In addition, the methodology of combining the CAD, CAE, and CAM to wood products design was proofed efficient, economic, and feasible, and can be also used in design of other products.

Engineering design and the impact of digital technology from computer-aided engineering to industrial metaverses: A perspective

Digital technology for engineering design is evolving from computer-aided engineering tools via digital twins to industrial metaverses. These advances are resolving many of the challenges associated with implementing concurrent design and enabling larger design domains to be considered and designs to be developed, reviewed and demonstrated more rapidly and with a wider range of stakeholders. However, the new technology is also creating new challenges associated with confidence in digital representations and with methods of working with a rapidly evolving design. These challenges need to be addressed so that radical new designs of complex systems can be produced quickly to support society in addressing the evolving crisis of climate change.

Enhancing Building Energy Efficiency through Building Information Modeling (BIM) and Building Energy Modeling (BEM) Integration: A Systematic Review

With the ever-increasing population and historic highest energy demand, the energy efficiency of buildings is becoming crucial. Architectural firms are moving from traditional Computer-Aided Design (CAD) to BIM. However, nearly 40% of the energy consumption is due to buildings. Therefore, there is a need to integrate BIM with Building Energy Modeling (BEM), which presents an innovative opportunity to demonstrate the potential of BIM to minimize energy consumption by integrating building information software with data from existing energy-efficient building automation systems (EBAS). BEM is a form of computational analysis that can be used in conjunction with BIM or Computer-Aided Engineering (CAE) systems. In this paper, an attempt has been made to explore the existing literature on BIM and BEM and identify the effect of the integration of BEM in BIM in the design phase of the project. A recent survey from the last ten years (2012 to 2023) was carried out on Google Scholar, Web of Science, Science Direct, and Scopus databases. Inclusion/exclusion criteria were applied, and papers were scrutinized. From the results, it can be observed that the convergence of BIM and BEM is found to be useful in practical applications; however, projects with short life cycles might not be suitable for this solution. Challenges exist in the interoperability tools which have restrictions on data exchange. Binary translation is found to be the most suitable candidate for data exchange. The analysis further showed that the most used program for integrating BIM/BEM is Green Building Studio developed by Autodesk to improve construction and operational efficiencies.