Reverse Engineering Research Articles

Enzymatic promiscuity and underground reactions accounted for the capability of Escherichia coli to use the non-natural chemical synthon 2,4-dihydroxybutyric acid as a carbon source for growth

2,4-dihydroxybutyric acid (DHB) and 2-keto-4-hydroxybutyrate (OHB) are non-natural molecules obtained through synthetic pathways from renewable carbon source. As they are structurally similar to lactate and pyruvate respectively, they could possibly interfere with the metabolic network of Escherichia coli. In fact, we showed that DHB can be easily oxidized by the membrane associated L and D-lactate dehydrogenases encoded by lldD, dld and ykgF into OHB, and the latter being cleaved into pyruvate and formaldehyde by several pyruvate-dependent aldolases, with YagE being the most effective. While formaldehyde was readily detoxified into formate, Escherichia coli K12 MG1655 strain failed to grow on DHB despite of the production of pyruvate. To find out the reason for this failure, we constructed a mutant strain whose growth was rendered dependent on DHB and subjected this strain to adaptive evolution. Genome sequencing of the adapted strain revealed an essential role for ygbI encoding a transcriptional repressor of the threonate operon in this DHB-dependent growth. This critical function was attributed to the derepression of ygbN encoding a putative threonate transporter, which was found to exclusively transport the D form of DHB. A subsequent laboratory evolution was carried out with E. coli K12 MG1655 deleted for ΔygbI to adapt for growth on DHB as sole carbon source. Remarkably, only two additional mutations were disclosed in the adapted strain, which were demonstrated by reverse engineering to be necessary and sufficient for robust growth on DHB. One mutation was in nanR encoding the transcription repressor of sialic acid metabolic genes, causing 140-fold increase in expression of nanA encoding N-acetyl neuraminic acid lyase, a pyruvate-dependent aldolase, and the other was in the promoter of dld leading to 14-fold increase in D-lactate dehydrogenase activity on DHB. Taken together, this work illustrates the importance of promiscuous enzymes in underground metabolism and moreover, in the frame of synthetic pathways aiming at producing non-natural products, these underground reactions could potentially penalize yield and title of these bio-based products.

Estimating the Cowper–Symonds Parameters for High-Strength Steel Using DIC Combined with Integral Measures of Deviation

Cowper–Symonds parameters were estimated for the complex-phase high-strength steel with a commercial name of SZBS800. The parameter estimation was based on a series of conventional tensile tests and unconventional high-strain rate experiments. The parameters were estimated using a reverse engineering approach. LS-Dyna was used for numerical simulations, and the material’s response was modelled using a piece-wise linear plasticity model with a visco-plastic formulation of the Cowper–Symonds material model. A multi-criteria cost function was defined and applied to obtain a response function for the parameters p and C. The cost function was modelled with a response surface, and the optimal parameters were estimated using a real-valued genetic algorithm. The main novelty and innovation of this article is the definition of a cost function that measures a deviation between the deformed geometry of the flat plate-like specimens and the results of the numerical simulations. The results are compared to the relevant literature. A critical evaluation of our results and references is another novelty of this article.

Developing a framework for enhancing security testing of android applications

Mobile applications have advanced a lot and now offer several features that help make our lives easier. Android is currently the most popular mobile operating system, and it is susceptible to exploitation attempts by malicious entities. This has led to an increased focus on the security of Android applications. This dissertation proposed the development of a framework which provides a systematic approach to testing the security of Android applications. This framework was developed based on a comprehensive review of existing security testing methodologies and tools. In achieving the study objectives, a test application was run on an emulator, Burp Suite was used as a proxy tool to capture HTTP and HTTPS traffic for analysis, reverse engineering was carried out, static and dynamic analysis were executed, network traffic was captured and analysed with tcpdump and Wireshark, intent sniffing was carried out, fuzz testing was discussed, and a proof-of-concept tool (automation script) was developed. This work covers various aspects of Android applications’ security testing, and the proposed framework provides developers with a practical and effective approach to testing the security of their Android applications, thereby improving the overall security of the Android application ecosystem.

Comparison of the biomechanical effects of the post-core crown, endocrown and inlay crown after deep margin elevation and its clinical significance

BackgroundThe purpose of this in vitro study was to compare and evaluate the stress distribution of maxillary first premolar residual crowns restored with post-core crowns, endocrowns and inlay crowns after deep margin elevation, to explore the fitting restoration for residual crowns using finite element analysis.MethodsA healthy complete right maxillary first premolar from a male adult was scanned by cone beam computed tomography (CBCT). The finite element model of the tooth was established by reverse engineering software such as Mimics, Geomagic and Hypermesh. On this basis, the residual crown model after deep margin elevation was made, and the experimental group models were divided into three groups, those restored with post core crowns, endocrowns and inlay crowns. Vertical and oblique static loads were applied to the experimental models to simulate the force on the tooth during mastication (the loading position was located in the central fossa of the occipital surface, and the load was 100 N) using Abaqus software.ResultsThe peak value and distribution of von Mises stress in each part of the experimental model were observed. After deep margin elevation, the peak dentin von Mises stresses were lower than the tensile strength of normal dentin in the post-core crown, endocrown, and inlay crown groups; the lowest stress results were found in the post-core crown group for the dentin, restoration, enamel, and deep margin elevation (DME) layers under vertical and oblique loading. In terms of stress distribution clouds, the peak stresses in the dentin tissue were located in the apical 1/3 of the root after postcore crown restorations for both loads, while stress concentrations were evident in the cervical and root areas after endocrown and inlay crown restorations; regardless of the load and restoration method, the corresponding stress concentration areas appeared at the junction of the DME and dentin tissue at the loading site of the restorations;ConclusionsPost-core crowns, endocrowns and inlay crowns can be used to restore residual crowns after deep margin elevation, and post-core crowns can better protect the residual tooth tissue.

Twin support vector regression for characterizing uncertainty in surface reconstruction

Surface reconstruction plays a pivotal role in various fields, including reverse engineering, and oil and gas exploration. However, errors in available data and insufficient surface morphology information often introduce uncertainty into the reconstruction. It is crucial to accurately characterize and visualize the uncertainty in surface reconstruction for risk analysis and planning further data collection. To this end, this paper proposes an uncertainty characterization method based on twin support vector regression. First, various modeling data are effectively integrated and the information contained in the high-confidence sample is efficiently utilized through the uncertainty interval generated by quantiles and upper/lower bound constraints. Second, well-path points are incorporated by imposing inequality constraints on the corresponding prediction points. Finally, in order to reduce computation time, the problem of uncertainty characterization is formulated as two smaller-scale quadratic programming. The results obtained from a real fault dataset and a synthetic dataset validate the effectiveness of the proposed method. When well data are available, the generated uncertainty envelopes are constrained by well data, which can partially mitigate reconstruction uncertainties.

Modeling and Validation of Rabbit Tibia Bone by Reverse Engineering

In the medical field, 3D modeling and prototyping of hard or soft tissues of living organisms provides great convenience for surgeons before the operation and during the simulation phase of the operation. In this study, 3D regular mesh and prototype models were created from normal CT data of the right tibia bone of a New Zealand albino rabbit and the errors occurring during this creation were compared. According to the results obtained, the lowest errors occurred in the TL dimension, while the largest errors occurred in the ITDD dimension. The measured error amounts vary between 0.8% and 7.2%. Considering these error margins compared to similar studies, it is seen that the modeling is quite normal and a satisfactory way to simulate surgeons has been created. Key Words: Rabbit Tibia, 3D Bone Modeling, Additive Manufacturing

Devising a methodology for prototyping convex-concave parts using reverse-engineering technology providing the predefined geometric accuracy of their manufacturing

The object of this paper is the geometric accuracy of the acquired portrait from the 3D printed full-scale sample in the reduced size of the convex-concave parts compared to the correspondingly reduced ideal one. The subject of research is reverse engineering and additive technology for manufacturing convex-concave parts for mechanical engineering (ME). A new prototyping methodology for convex-concave parts of mechanical engineering objects has proposed. Underlying the methodology is the use of the scaled (by reducing in size) ideal portrait of the 3D scanned original part. The decision to start the production is made by comparing the geometry of the portrait acquired from the 3D printed sample in reduced size with the ideal one, provided that the values are within the tolerance range. The following results were obtained. A design and technological analysis of the blade of the pumped hydroelectric power station was performed, after which a 3D scanner and a 3D printer were selected. A 3D scan of the blade with the formation of a portrait in the STL format file was implemented, as well as its refinement into an ideal one. From the geometric features and shapes of the blade, as well as the technical characteristics of the 3D printer, the percentage of reducing the sample for printing (by 75 % of the original dimensions) was calculated. According to the rated dimensions of the original part and the reduced sample, the tolerance field was set for the size: 0.6 mm and 0.25 mm, respectively, at 12 quality of the part’s manufacturing accuracy. Inspection of the printed sample and comparison with the correspondingly reduced ideal portrait revealed a deviation from –0.123 to +0.120 mm, which is within the defined tolerance field for the manufactured reduced sample. The results of experimental studies confirmed the adequacy of the proposed methodology for prototyping the mechanical engineering parts and verified the theoretical foundations of reverse engineering for convex-concave parts of any large size by using a proportional reduction in the size of finished portraits

Brain-consistent architecture for imagination.

Imagination represents a pivotal capability of human intelligence. To develop human-like artificial intelligence, uncovering the computational architecture pertinent to imaginative capabilities through reverse engineering the brain's computational functions is essential. The existing Structure-Constrained Interface Decomposition (SCID) method, leverages the anatomical structure of the brain to extract computational architecture. However, its efficacy is limited to narrow brain regions, making it unsuitable for realizing the function of imagination, which involves diverse brain areas such as the neocortex, basal ganglia, thalamus, and hippocampus. In this study, we proposed the Function-Oriented SCID method, an advancement over the existing SCID method, comprising four steps designed for reverse engineering broader brain areas. This method was applied to the brain's imaginative capabilities to design a hypothetical computational architecture. The implementation began with defining the human imaginative ability that we aspire to simulate. Subsequently, six critical requirements necessary for actualizing the defined imagination were identified. Constraints were established considering the unique representational capacity and the singularity of the neocortex's modes, a distributed memory structure responsible for executing imaginative functions. In line with these constraints, we developed five distinct functions to fulfill the requirements. We allocated specific components for each function, followed by an architectural proposal aligning each component with a corresponding brain organ. In the proposed architecture, the distributed memory component, associated with the neocortex, realizes the representation and execution function; the imaginary zone maker component, associated with the claustrum, accomplishes the dynamic-zone partitioning function; the routing conductor component, linked with the complex of thalamus and basal ganglia, performs the manipulation function; the mode memory component, related to the specific agranular neocortical area executes the mode maintenance function; and the recorder component, affiliated with the hippocampal formation, handles the history management function. Thus, we have provided a fundamental cognitive architecture of the brain that comprehensively covers the brain's imaginative capacities.

Lock-in Thermography for the Localization of Security Hard Blocks on SoC Devices

AbstractLocalizing security-relevant hard blocks on modern System-on-Chips for physical attacks, such as side-channel analysis and fault attacks, has become increasingly time-consuming due to ever-increasing chip-area and -complexity. While this development increases the effort and reverse engineering cost, it is not sufficient to withstand resolute attackers. This paper explores the application of camera-based lock-in thermography, a nondestructive testing method, for identifying and localizing security hard blocks on integrated circuits. We use a synchronous signal to periodically activate security-related functions in the firmware, which causes periodic temperature changes in the activated die areas that we detect and localize via an infrared camera. Using this method, we demonstrate the precise detection and localization of security-related hard blocks at the die level on a modern SoC.

Generation and evaluation of unimaginable three-dimensional structural joints using generative adversarial networks

Compared to the increasingly programmable and automated structural analysis methods, the current joint design suffers from long design time, poor quality and a low degree of automation. Developing an efficient and intelligent method to generate structurally novel and high-performing joints has become an urgent task. This paper combines artificial intelligence, topology optimization and reverse engineering techniques to develop a method named HD-JointGEN, and elaborates the idea and implementation steps of this method through an actual engineering example of a single-layer reticulated shell structure. The joints generated in batch by HD-JointGEN are analyzed and evaluated, revealing that the selected representative joint can reduce self-weight by 29.55%, maximum displacement by 0.99%, and maximum equivalent stress by 1.28% compared to the topology optimization joint. HD-JointGEN not only automatically generates a variety of innovative and previously unimaginable joints but also offers design solutions with superior force performances. It leads the research on intelligent generative design of the connection in complex three-dimensional structures and has broad application prospects.

Experimental Fitting of Efficiency Hill Chart for Kaplan Hydraulic Turbine

The development of hydroelectric technology and much of the “knowledge” on hydraulic phenomena derive from scale modeling and “bench” tests to improve machinery efficiency. The result of these experimental tests is mapping the so-called “hill chart”, representing the “DNA” of a turbine model. Identifying the efficiency values as a function of the specific parameters of the flow and energy coefficient (which both identify the operating point) allows us to represent the complete behavior of a turbine in hydraulic similarity with the original model developed in the laboratory. The present work carries out a “reverse engineering” operation that leads to the definition of “an innovative research model” that is relatively simple to use in every field. Thus, from the experimental survey of the degree of efficiency of several prototypes of machines deriving from the same starting model, the hill chart of the hydraulic profile used is reconstructed. The “mapping” of all the characteristic quantities of the machine, together with the physical parameters of the regulating organs of a four-blade Kaplan turbine model, also made it possible to complete the process, allowing to identify not only the iso-efficiency regions but also the curves relating to the trend of the angle of the impeller blades, the specific opening of the distributor, and the identification of critical areas of cavitation. The development of the hill chart was made possible by investigating the behavior of 33 actual prototypes and 46 characteristic curves derived from the same reference model based on practical experiments for finding the optimal blade distributor “setup curve”. To complete this, theoretical characteristic curves of “not physically realized” prototypes were also mapped, allowing us to complete the regions comprising the diagram. The study of the unified hill charts found in previous documentation of the most famous manufacturers was of great help. Finally, the validation of the “proposed procedure” was obtained through the experimental survey of the actual efficiency of the new prototype based on the theoretical values defined in the design phase on the chart obtained with the method described.

Covalent penicillin-protein conjugates elicit anti-drug antibodies that are clonally and functionally restricted

Many archetypal and emerging classes of small-molecule therapeutics form covalent protein adducts. In vivo, both the resulting conjugates and their off-target side-conjugates have the potential to elicit antibodies, with implications for allergy and drug sequestration. Although β-lactam antibiotics are a drug class long associated with these immunological phenomena, the molecular underpinnings of off-target drug-protein conjugation and consequent drug-specific immune responses remain incomplete. Here, using the classical β-lactam penicillin G (PenG), we probe the B and T cell determinants of drug-specific IgG responses to such conjugates in mice. Deep B cell clonotyping reveals a dominant murine clonal antibody class encompassing phylogenetically-related IGHV1, IGHV5 and IGHV10 subgroup gene segments. Protein NMR and x-ray structural analyses reveal that these drive structurally convergent binding modes in adduct-specific antibody clones. Their common primary recognition mechanisms of the penicillin side-chain moiety (phenylacetamide in PenG)—regardless of CDRH3 length—limits cross-reactivity against other β-lactam antibiotics. This immunogenetics-guided discovery of the limited binding solutions available to antibodies against side products of an archetypal covalent inhibitor now suggests future potential strategies for the ‘germline-guided reverse engineering’ of such drugs away from unwanted immune responses.

Phase Field Damage Framework for Modeling Thin-Film Silicon Anodes in All-Solid-State Batteries

Recent advancements in solid electrolyte research have revived interest in the concept of silicon anodes for All-Solid-State Batteries (aSSBs). Tan et al. have recently proposed stable cyclic performance of micro-grain size pure silicon anodes paired with sulfide-based solid electrolytes [1]. This development has opened pathways toward potential aSSBs without encountering dendrite growth issues. This rediscovery of the thin-film a-silicon anodes concept has sparked computational interest in simulating the fracture-chemo-mechanical silicon lithiation mechanism. Understanding chemical reactions during lithiation and crack evolution during de-lithiation processes are intriguing topics. Especially, elastic-plastic deformation coupled with phase-field continuous fracture is crucial in comprehending the underlying physics and enhancing performance of battery cell through reverse engineering approaches.In this work, we develop a thermodynamically consistent deformation-diffusion-damage coupled framework to model the evolution of dense, thin-film-like a-silicon anodes during lithiation and delithiation. During delithiation, tensile stress develops inside the film as the lithiated film overcomes the initial stack pressure and compressive stress prevalent during lithiation. As tensile stress and strain evolve, randomly distributed weak spots lead to crack nucleation. This fracture occurs throughout the silicon film, forming sharp vertical cracks, and depending on surface conditions along the solid-state electrolyte, some interfacial cracks may emerge, leading to permanent contact loss and resulting in capacity reduction.From the model, we observed “mud crack” like phenomena, where crack distribution is not controlled by particle’s property, but entire cluster’s thickness matters. While flat model suggests that one that nucleate the crack was weak spots where they make stress concentration over entire body, whether they can evolve into big vertical crack mostly governed by connectivity of such weak spot maps. However, from our interface roughness model, what governs the crack evolution most was not the randomly distributed weak spot, but its geometric relative thickness difference between one another. Due to manufacturing process, perfect interface is hard to be achieved and such geometric irregularity always exist, thus, additive and binder studies along the silicon anode and its interface between sse would be key to achieve long and stable life span for a-silicon based aSSBs. Reference [1] Tan, Darren HS, et al. "Carbon-free high-loading silicon anodes enabled by sulfide solid electrolytes." Science 373.6562 (2021): 1494-1499.

Quantum Dots and Molecular Junctions as Energy Filters for Thermal-to-Electric Energy Conversion

The thermoelectric conversion of heat into electricity requires a form of energy filtering, that allows hot electrons to pass while blocking cold electrons. The energy conversion efficiency is determined by the details of the energy filtering, with an infinitely sharp (delta function) transmission spectrum allowing near ideal (Carnot) efficiency. [1]I will introduce this concept and report on a proof-of-performance experiment based on a quantum dot embedded into a single, semiconductor nanowire. This near-ideal quantum-dot heat engine realized power production at maximum power with Curzon-Ahlborn efficiency as well more than 70% of Carnot efficiency at maximum efficiency settings [2].To further enhance efficiency at maximum power one wishes to shape the transmission function to allow a spectrum of warmer electrons to pass while still completely blocking cold electrons. This may be achieved by exploiting quantum interference phenomena to block low-energy electron transmission by destructive interference, and to thus sculpt the transmission function of quantum dots or molecular junctions.[4] In contrast to quantum dots, molecular junctions have the advantage that they can be used at room temperature and can be produced, in principle, cheaply and scalable. To systematically explore the effect of quantum interferences, we designed and synthesized a new class of porphyrins that are expected to feature destructive quantum interference in single molecule junctions with gold electrodes and may thus show high thermopower, as well as a control that does not. We performed detailed experimental single-molecule break-junction studies of conductance and thermopower on porphyrin molecular junctions. We find a somewhat better thermoelectric performance for the porphyrin where we expect destructive interference. However, the predicted large difference in conductance and thermopower is not supported by our experimental findings.[4]Finally, I will also briefly discuss the potential application of the concepts and systems presented here in hot-carrier photovoltaics, as an approach to increasing photovoltaic energy conversion efficiency beyond current limits.[1] T.E. Humphrey et al., Reversible Quantum Brownian Heat Engines for Electrons. Phys. Rev. Lett., 89, 116801 (2002)[2] M. Josefsson et al. A quantum-dot heat engine operated close to thermodynamic efficiency limits. Nature Nanotechn. 13, 920 (2018)[3] O Karlström et al. Increasing thermoelectric performance using coherent transport. Phys. Rev. B 84, 113415 (2011)[4] H. Xu et al. Electrical Conductance and Thermopower of β-Substituted Porphyrin Molecular Junctions Synthesis and Transport. JACS 145 , 23541 (2023) Figure 1

Nine-grid Area Division Method: A New Ideal Bone Puncture Region for Percutaneous Vertebroplasty in Lumbar Spine.

Percutaneous vertebroplasty (PVP) is widely recognized as an efficacious intervention for alleviating low back pain resulting from osteoporotic vertebral compression fractures. The ideal bone puncture point is conventionally situated at the projection "left 10 points, right 2 points" of the pedicle in the lumbar spine. Determining the optimal bone puncture point represents a critical and complex challenge. The accuracy of percutaneous vertebroplasty (PVP) is primarily influenced by the proficiency of the operating surgeons and the utilization of multiple fluoroscopes during the conventional procedure. Incidences of puncture-related complications have been documented globally. In an effort to enhance the precision of the surgical technique and reduce the occurrence of puncture-related complications, our team applied the "Nine-grid Area Division Method" for PVP in the lumbar spine to modify the traditional procedure. There is potential to decrease the number of puncture times, the radiation exposure dosage, and the duration of surgical procedures. This protocol introduces the definition of the "Nine-grid Area Division Method" and describes the process of modeling target vertebrae DICOM imaging data within medical imaging processing software, simulating operations within a 3-D model, refining the 3-D model using reverse engineering production software, reconstructing the vertebral engineering model within 3-D modeling design software, and utilizing surgical data to determine safe entry regions for pedicle projection. By employing this methodology, surgeons can effectively identify appropriate puncture points with precision and ease, thereby reducing the intricacies associated with puncturing and enhancing the overall accuracy of surgical procedures.

Prioritizing privacy and presentation of supportable hypothesis testing in forensic genetic genealogy investigations.

Investigative leads are not generated by traditional forensic DNA testing, if the source of the forensic evidence or a 1stdegree relative of unidentified human remains is not in the DNA database. In such cases, forensic genetic genealogy (FGG) can provide valuable leads. However, FGG generated genetic data contain private and sensitive information. Therefore, it is essential to deploy approaches that minimize unnecessary disclosure of these data to mitigate potential risks to individual privacy. We recommend protective practices that need not impact effective reporting of relationship identifications. Examples include performing one-to-one comparisons of DNA profiles of third-party samples and evidence samples offline with an "air gap" to the internet and shielding the specific shared single nucleotide polymorphisms (SNP) states and locations by binning adjacent SNPs in forensic reports. Such approaches reduce risk of unwanted access to or reverse engineering of third-party individuals'genetic data and can give these donors greater confidence to support use of their DNA profiles in FGG investigation.

Reverse Engineering: Techniques, Applications, Challenges, Opportunities

Reverse Engineering: Techniques, Applications, Challenges, Opportunities

Deep learning of plausible bandgaps in dispersion curves of phononic crystals

Phononic crystals represent an interesting class of metamaterials that can be utilized to regulate or manipulate vibration, sound propagation, and thermal transport. Their useful features mainly arise from the bandgaps in their dispersion curves, preventing the passage of waves within specific frequency ranges. However, it is often costly and time-consuming to obtain the dispersion curves, and the reverse engineering of phononic crystals to have pre-defined bandgaps possesses even greater challenges. In this research, we address this issue by employing a deep artificial neural network to predict the bandgap ratio and the characteristics of plausible bandgaps, focusing on the localized resonance in columnar phononic crystals. We utilized two geometric parameters, i. e. the ratio of diameter and height of the cylindrical resonators relative to the lattice constant, achieving a determination coefficient of 0.9993 for predicting the characteristics of the bandgaps and 0.9827 for predicting the bandgap ratio. To verify the model and better understand its behavior, we introduce Shapley values. These values provide a comprehensive insight into how each geometric parameter influences the predicted bandgap ratios.

GNN-Based Reverse Engineering Protection Using Obfuscation Through Electromagnetic Interference

To combat PCB design reverse engineering and protect intellectual property, a method of obfuscation is developed. Noise generating traces are placed alongside the true circuit, separated by false non-conductive vias visually indistinguishable from regular ones. If the false vias are copied as real conductive vias in illegitimate replications, signals will be distorted, leading to poor performance. The deliberate placement of the generators separated by false vias is tested using a machine learning algorithm (MLA) employing a signal integrity database to determine the most vulnerable traces in the PCB based on their physical properties and interconnections.

REVERSE ENGINEERING MODELING PROCESSING AND FABRICATION OF VORONOI PERFORATED ANKLE-FOOT ORTHOSIS

The ankle may not function optimally because of an ankle foot injury due to torn ligaments or foot drop, a post-stroke effect of hemiplegia. One treatment that can be done for sufferers of ankle foot injury and foot drop is using an ankle foot orthosis (AFO). Reverse engineering (RE) and additive manufacturing (AM) technologies can be utilized within the medical domain, specifically for producing prosthetic devices and orthoses that include optimal fit, lightweight characteristics, and cost-effectiveness. This study aims to create an optimized design for an ankle-foot orthosis by utilizing reverse engineering techniques, followed by an analysis of its performance using finite element simulation. The research process involved several key steps, namely 3D Scanning, CAD modeling, model analysis, and 3D printing. The findings of the model study after the implementation of Voronoi ventilation holes indicated that the highest equivalent stress observed in the model, with a shell element thickness of 1.4 mm, amounted to 21.12 MPa. This result represented an elevation of 11.74% compared to the model before introducing Voronoi ventilation holes. Nevertheless, there was a reduction in the model's mass by 20.3%, specifically from an initial weight of 400.86 grams to a final weight of 319.51 grams. On the contrary, despite a fall in the safety factor, it continues to be considered safe, with a value of 2.84.