Computer-aided Design Process Research Articles

Zeolite-Y-catalyst production from locally sourced Meta-kaolin: Computer-Aided scale-up process design and economic analysis with Monte-Carlo-Simulation

Production of zeolite-Y catalyst from natural substrate has been a research trend in the scientific community. Published articles revealed that zeolite-Y recovery from locally sourced metakaolin is confined to laboratory practice. Scale-up process design and its economic feasibility for zeolite-Y catalyst recovery are rarely found in the scientific bibliography. Therefore, this study presented conceptual scale-up process design, base-case techno-economics and Monte-Carlo simulation of zeolite Y recovery from Nigerian metakaoline. ASPEN Base Case Simulation (ABCS), scale-up design and economics were accomplished using inherent design and costing algorithms in ASPEN Batch Process Developer (ABPD) V10. Process economic parameters: Net Present Value (NPV), Internal Rate of Return (IRR), Return on Investment (ROI) and Payback Time (PBT), were modelled and optimized using Design Expert V13 software; while zeolite Unit Production Cost (UPC), Annual Production Cost (APC), Total Capital Investment (TCI) and interest/discount rate were considered as model inputs. Monte-Carlo Simulation (MCS) in Crystal Ball Oracle software was used to perform the sensitivity and uncertainty analyses. The base-case techno-economic results of process design of 600,000 kg/year zeolite production gave batch size 5000 kg/batch with 104 batches/year, batch time (4149 min), TCI ($15,930,306), APC ($147,145), NPV ($41,983,375), ROI (38.13 %) and PBT (2.14 years). The coefficient of determination (R2) of the economic models were 0.9978, 0.9989 and 0.9986 for NPV, ROI and IRR respectively. The optimum economic variables that maximized synthesis of 5000 kg/batch zeolite Y are UPC ($11.68), APC ($100,033) and TPC ($15,930,200). MCS uncertainty for NPV, IRR and ROI are negligible. Therefore, this study demonstrated that scale-up zeolite-Y production from the local substrate is economically feasible.

Prediction of stability constants of metal-ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity.

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted logK values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal-ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R2 of 0.959 ± 0.007). For relative logK predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. We showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.

TEM Image Analysis and Simulation Physics for Two-Step Recrystallization of Discretely Amorphized C3H5-Molecular-Ion-Implanted Silicon Substrate Surface

In this study, we investigate the initial rapid recrystallization of a discretely amorphized C3H5-molecular-ion-implanted silicon (Si) substrate surface in the subsequent thermal annealing treatment through the analysis of plan-view transmission electron microscopy (TEM) images and technology computer-aided design (TCAD) process simulation. In the approach of the analysis of the plan-view TEM image of the Si substrate surface, we found that initial rapid recrystallization occurs in the intermediate regions between the residual crystalline and discrete amorphous regions formed in the C3H5-molecular-ion-implanted Si substrate surface. In addition, the TCAD process simulation results indicate that the intermediate regions correspond to the amorphous pockets formed around the discrete amorphous regions in the C3H5-molecular-ion-implanted Si substrate surface and are recrystallized preferentially during the short thermal annealing time. These plan-view TEM image analysis and TCAD process simulation results reveal a two-step recrystallization of the discretely amorphized C3H5-molecular-ion-implaned Si substrate surface. After the initial rapid recrystallization of amorphous pockets in the 1st step, the recrystallization of discrete amorphous regions starts in the 2nd step. The incubation period between the 1st and 2nd steps is the time required to recrystallize the amorphous pockets around the discrete amorphous regions completely and redefine the amorphous/crystalline interface.

Translucency and Strength of Lithium Disilicate for Computer-Aided Design and Manufacturing at Different Thermal Temperatures and Thicknesses: An In Vitro Study.

To manufacture dental restorations composed of lithium disilicate (LD) through the computer-aided design and manufacturing (CAD/CAM) process, thermal refinement is an essential process that can affect the optical and mechanical properties of ceramics. In this study, we aimed to evaluate the translucency and flexural strength of lithium disilicate glass-ceramic for CAD/CAM using different thermal refinement schedules and thicknesses by measuring the total transmission of light through the specimen and calculating the peak load of the specimen until fracture in a piston-on-three-ball test, respectively. The results showed that a lower translucency was exhibited in thicker specimens, and the flexural strength decreased in the order of 1.0, 0.5, and 2.0 mm (p < 0.05). The lithium disilicates thermally refined at a heat of 820 degrees were shown to have the highest biaxial flexural strength (p < 0.05). These findings suggest that it is possible to adjust transparency and strength according to the clinical situation by choosing an appropriate thickness and thermal refinement process.

Is dynamic occlusal design necessary for anterior guidance recovery in the computer-aided design process? An in vitro study

ObjectivesThis study aimed to assess the effectiveness of patient-specific motion in restoring anterior guidance and to investigate the influence of occlusal plane position within a virtual articulator on the design of the anterior guide slope for incisors. MethodsTwenty participants' intraoral scan, occlusal plane position, and jaw motion data were recorded. The maxillary anterior teeth were virtually prepared, and the crowns were designed based on average virtual articulator (AVR), personalized virtual articulator (ART), and patient-specific motion (PSM). The anterior guide slope of maxillary central incisors (S1, S2, Sc, Sp) and the mesio-distal angle (MDA) of the canine of prostheses were compared to that of natural teeth (NAT). One-Way ANOVA was utilized to evaluate the effectiveness of the three methods in restoring the anterior guidance of maxillary anterior teeth. ResultsThe comparison of Sp and MDA showed no significant difference between the PSM and NAT groups (p > 0.05). However, Sp of the ART group was significantly smaller, while MDA was higher than that of the NAT group (p < 0.05). Sp did not differ significantly (p > 0.05) when the angle of the occlusal plane (AOP) was small. As the AOP increased, Sp of the ART and AVR groups were significantly smaller than that of the NAT group (p < 0.05). With a large AOP, Sp of the ART group was notably smaller than that of the NAT group (p < 0.05), while there was no significant difference between the AVR and NAT groups (p > 0.05). ConclusionsOcclusal design based on patient-specific motion proved more effective in restoring natural anterior guidance. The anterior guidance of prostheses designed using a virtual articulator was influenced by occlusal plane position. Clinical SignificanceThe utilization of a jaw motion tracer facilitated the transfer of personalized occlusal plane positions and recorded jaw motion, which can be integrated into the digital prosthetic workflow for virtual occlusion adjustment. Occlusal design based on patient-specific motion more effectively restored lingual guidance of maxillary anterior crowns.

Research on Teaching Reform and Innovation of Computer-aided Process Planning Courses

The innovative research on the teaching reform of computer-aided process design course aims to improve the quality and effectiveness of teaching, and cultivate talents who are more in line with social needs. By introducing the latest technology and theories in the industry, adopting various teaching methods, and strengthening practical teaching, measures are taken to stimulate students' interest and enthusiasm in learning, and improve their practical ability and comprehensive quality.

3D process simulation-assisted device failure analysis with virtual defect injection in IC layout

The development and use of nanotechnology has enabled the creation of submicron electronic devices with unprecedented levels of functionality, speed, and efficiency. While most of the semiconductor industry and its consumers are becoming increasingly dependent on nanoelectronics, these devices are becoming more susceptible to defects and transient faults. Non-Visual Defects (NVD) is a category of semiconductor material and process induced defect that cause electrical failures but are not detected with visual wafer inspection tools (Findlay et al., 2016 [1] and Kim et al., 2009 [10]) or with fault localization tools. Devices with NVD may fail at any stage of their life cycle and may benefit from complex Failure Analysis (FA) investigations including software support to analyze design and diagnostic data. For a higher FA success rate, these investigations can be further supplemented with Technology Computer-Aided Design (TCAD) Process Simulation software to simulate a failure prior to actual physical analysis on limited device samples. In this work, we will showcase an innovative technique for simulating NVD using a 3D process model to pinpoint the exact process step where the defect was introduced. By injecting a new virtual defect layer (which can be autonomously introduced by an FA engineer) in the original device data, we can emulate the failing device. We also present a real-life case study where defect simulation correlates well with the actual Transmission Electron Microscope (TEM) cross-section results.

Extrusion-based 3D printing of osteoinductive scaffolds with a spongiosa-inspired structure.

Critical-sized bone defects resulting from trauma, inflammation, and tumor resections are individual in their size and shape. Implants for the treatment of such defects have to consider biomechanical and biomedical factors, as well as the individual conditions within the implantation site. In this context, 3D printing technologies offer new possibilities to design and produce patient-specific implants reflecting the outer shape and internal structure of the replaced bone tissue. The selection or modification of materials used in 3D printing enables the adaption of the implant, by enhancing the osteoinductive or biomechanical properties. In this study, scaffolds with bone spongiosa-inspired structure for extrusion-based 3D printing were generated. The computer aided design process resulted in an up scaled and simplified version of the bone spongiosa. To enhance the osteoinductive properties of the 3D printed construct, polycaprolactone (PCL) was combined with 20% (wt) calcium phosphate nano powder (CaP). The implants were designed in form of a ring structure and revealed an irregular and interconnected porous structure with a calculated porosity of 35.2% and a compression strength within the range of the natural cancellous bone. The implants were assessed in terms of biocompatibility and osteoinductivity using the osteosarcoma cell line MG63 and patient-derived mesenchymal stem cells in selected experiments. Cell growth and differentiation over 14days were monitored using confocal laser scanning microscopy, scanning electron microscopy, deoxyribonucleic acid (DNA) quantification, gene expression analysis, and quantitative assessment of calcification. MG63 cells and human mesenchymal stem cells (hMSC) adhered to the printed implants and revealed a typical elongated morphology as indicated by microscopy. Using DNA quantification, no differences for PCL or PCL-CaP in the initial adhesion of MG63 cells were observed, while the PCL-based scaffolds favored cell proliferation in the early phases of culture up to 7days. In contrast, on PCL-CaP, cell proliferation for MG63 cells was not evident, while data from PCR and the levels of calcification, or alkaline phosphatase activity, indicated osteogenic differentiation within the PCL-CaP constructs over time. For hMSC, the highest levels in the total calcium content were observed for the PCL-CaP constructs, thus underlining the osteoinductive properties.

Computer-aided batch process design, techno-economic and uncertainty analyses of bio-clarified water recovery from south-eastern Nigerian brewery wastewater

Biocoagulation-flocculation-sedimentation (bioclarification) is one of the main wastewater treatment techniques. Despite its effectiveness in treating brewery wastewater for water reuse, the scale-up process for the reclaimed brewery water from wastewater has rarely been documented in the literature. This study presents the computer-aided process design, techno-economic and uncertainty analyses of bioclarified water production from brewery wastewater. The base-case simulation model, process scale-up design and economics were performed in Aspen Batch Process Developer. Process profitability indices (Net Present Value: (NPV), Internal Rate of Return: (IRR) and Payback Time: PBT) were evaluated in a user-defined developed Microsoft-excel version 2018. Monte-Carlo-Simulation in Crystal-Ball-Oracle software was used to perform the sensitivity and uncertainty analyses. The process scale-up simulation results gave annual production capacity (45,000,000 L/year), batch size (9800 L/batch) and annual number of batches produced (4564 batches/year). Base case capacity results showed that the total capital investment, NPV, IRR and PBT are $2,416,358.62, $2,790,608, 36% and 3.27years respectively. Sensitivity analysis shows that production capacity and product selling price have the highest contribution for both NPV and IRR respectively. Certainties of base-case model were 90.27% for the IRR and 99.51% for the NPV. This study showed that brewery wastewater bioclarification scale-up design is feasible.

Removable complete denture with a metal base: Integration of digital design and conventional fabrication techniques.

Digitally-designed removable complete dentures are typically composed of a resin denture base without a metal framework. However, metal denture bases are preferable as resin bases are more susceptible to fracture. Therefore, this article introduces a unique technique that integrates computer-aided design (CAD) and conventional resin processing for the fabrication of removable complete dentures with a metal framework. A maxillary complete denture with a metal base and a mandibular implant-retained overdenture reinforced with a metal framework were fabricated. The dentures were designed using CAD software and a tooth library. The denture bases were milled from wax disks, and artificial teeth were placed to complete the wax dentures. The metal frameworks were also designed using CAD software and produced via casting of printed resin patterns. Finally, conventional denture processing techniques were applied to obtain dentures with metal frameworks. A digitally designed, removable complete denture with a metal base can be successfully fabricated using the described technique, which merges digital design and conventional methods. This article demonstrates the feasibility and potential advantages of this innovative approach in denture fabrication. The presented technique provides the following advantages: digital design features, precise space above implant overdenture attachments for a metal framework, convenience of esthetic evaluation with printed trial dentures, long-term data storage and duplication, reliable bond between the artificial teeth and denture base, and enhanced strength of the removable complete denture due to the metal reinforcement.

Design and Development of a Novel 3-D Printed External Fixation Device for Fracture Stabilization

BackgroundAn external fixator is an orthopaedic device used to stabilize long bone fractures after high energy trauma. These devices are external to the body and fixed to metal pins going into non-injured areas of bone. They serve a mechanical function to maintain length, prevent bending, and resist torque forces about the fracture area. The purpose of this manuscript is to describe a design and prototyping process creating a low-cost entirely 3-D printed external fixator for fracture stabilization of extremity fractures. The secondary objective of this manuscript is to facilitate future advancements, modifications, and innovations in this area of 3-D printing in medicine.MethodsThis manuscript describes the computer aided design process using desktop fused deposition modeling to create a 3-D printed external fixator system designed for fracture stabilization. The device was created using the orthopaedic goals for fracture stabilization with external fixation. However, special modifications and considerations had to be accounted for given the limitations of desktop fused deposition modeling and 3-D printing with plastic polymers.ResultsThe presented device accomplishes the goals of creating a construct that can be attached to 5.0 mm metal pins, allows for modularity in placement orientations, and facilitates adjustable lengths for fracture care. Furthermore, the device provides length stability, prevention of bending, and resists torque forces. The device can be printed on a desktop 3-D printer using standard low-cost polylactic acid filament. The print time is less than two days and can be completed on one print bed platform.ConclusionsThe presented device is a potential alternative for fracture stabilization. The concept of a desktop 3-D printed external fixator design and method of production allows for numerous diverse applications. This includes assisting areas with remote or limited access to advanced medical care and large-scale natural disasters or global conflicts where large volumes of fractures exceed the local medical supply chain capabilities. The presented device creates a foundation for future devices and innovations in this fracture care space. Further research is needed on mechanical testing and clinical outcomes with this design and initiative in fracture care before clinical application.

Experimental investigation of the effect of lubricant change on automotive component

Manufacturing problems resulting from lubricant supplier changes are relatively common in automotive press shops. Simulations using computer-aided design (process and tool) detect a significant proportion of manufacturing problems before tools are physically produced. In modern forming codes, an enhanced Coulomb model is used to numerically model the friction phenomena associated with lubrication. In the laboratory condition, determining model parameters through physical measurement is challenging. As a result, it became necessary to design a device that could be utilized in industrial environments. In this study, we present the prediction of a manufacturing problem resulting from a change in the lubricant of an industrial sheet metal part. The measuring device has been developed based on the parameters of the friction model of the lubricant materials. The developed measuring device may be used to determine the pressure and velocity dependent friction model parameters. The measuring device can only measure a limited range of pressures and velocities, so the results are extended to a wider range using a mathematical method. The results are used to demonstrate the effect of lubricant material changes on the forming process using the AutoForm code.

Custom Silicone Distal Cup Designed and Fabricated Using 3D Optical Scanning and Additive Manufacturing to Improve Socket Fit of an Individual with Tranfemoral Amputation with Irregular Distal Residual Limb Morphology

ABSTRACT Introduction The study presents the design and manufacturing of a custom silicone distal cup, with a high spatial resolution, to fit inside the prosthetic liner for the treatment of irregular morphology at the distal residual limb of a patient with lower-limb amputation. This distal cup for the inside of the prosthetic liner has intricate interior features matching the shape of the distal residual limb to prevent localized high-pressure regions. Methods High-resolution 3D optical scanning, computer-aided design (CAD), and material extrusion (MEX) process for additive manufacturing of molds are three key techniques for designing and manufacturing this custom distal cup. A three-part mold for molding the distal cup with matching features was designed by CAD and fabricated by MEX. The subject evaluated the distal cup by walking using the distal cup before wearing the prosthetic liner in the lower-limb prosthesis. Results A custom silicone distal cup was fabricated using a 3D-printed mold and evaluated using a Prosthetic User’s Survey. Based on the survey, the insert has an acceptable comfort, suspension requirement, and ease of use. Conclusions The scan by high spatial resolution Space Spider optical scanner could capture detailed features of the distal residual limb. The resulting distal cup had the protrusion that functioned to separate the invaginations. The subject was satisfied with the distal cup based on the Prosthetic User’s Survey. Clinical Relevance The approach to fabricate the custom silicone distal cup using a high-resolution 3D optical scanner and a 3D-printed mold can be applied to fabricate the distal cup with intricate features for a patient with irregular morphology at the distal residual limbs.

A Scoping Review of Voxel-Model Applications to Enable Multi-Domain Data Integration in Architectural Design and Urban Planning

Although voxel models have been applied to address diverse problems in computer-aided design processes, their role in multi-domain data integration in digital architecture and planning has not been extensively studied. The primary objective of this study is to map the current state of the art and to identify open questions concerning data structuring, integration, and modeling and design of multi-scale objects and systems in architecture. Focus is placed on types of voxel models that are linked with computer-aided design models. This study utilizes a semi-systematic literature review methodology that combines scoping and narrative methodology to examine different types and uses of voxel models. This is done across a range of disciplines, including architecture, spatial planning, computer vision, geomatics, geosciences, manufacturing, and mechanical and civil engineering. Voxel-model applications can be found in studies addressing generative design, geomatics, material science and computational morphogenesis. A targeted convergence of these approaches can lead to integrative, holistic, data-driven design approaches. We present (1) a summary and systematization of the research results reported in the literature in a novel manner, (2) the identification of research gaps concerning voxel-based data structures for multi-domain and trans-scalar data integration in architectural design and urban planning, and (3) any further research questions.

A Semi-Supervised Learning Framework for Machining Feature Recognition on Small Labeled Sample

Automated machining feature recognition is an essential component linking computer-aided design (CAD) and computer-aided process planning (CAPP). Deep learning (DL) has recently emerged as a promising method to improve machining feature recognition. However, training DL-based recognition models typically require annotating large amounts of data, which is time-consuming and labor-intensive for researchers. Additionally, DL models struggle to achieve satisfactory results when presented with small labeled datasets. Furthermore, existing DL-based approaches require significant memory and processing time, thus hindering their real-world application. To address these challenges, this paper presents a semi-supervised learning framework that leverages both labeled and unlabeled data to learn meaningful visual representations. Specifically, self-supervised learning is utilized to extract prior knowledge from a large dataset without annotations, which is then transferred to improve downstream feature recognition tasks. Furthermore, we apply lightweight network techniques to two established feature recognizers, FeatureNet and MsvNet, to develop reduced-memory, computationally efficient models termed FeatureNetLite and MsvNetLite, respectively. To validate the effectiveness of the proposed approaches, we conducted comparative studies on the FeatureNet dataset. With only one training sample per class, MsvNetLite outperformed MsvNet by about 19%, whereas FeatureNetLite outperformed FeatureNet by approximately 20% in machining feature classification. On a common X86 CPU, MsvNetLite gained 6.68× improvement in speed over MsvNet, and FeatureNetLite was 2.49× faster than FeatureNet. The proposed semi-supervised learning framework shows a significant improvement in machining feature recognition on small labeled data while achieving the optimal balance between recognition accuracy and inference speed compared to other DL-based approaches.

Enabling the direct solution of challenging computer-aided molecular and process design problems: Chemical absorption of carbon dioxide

The search for improved CO2 capture solvents can be accelerated by deploying computer-aided molecular and process design (CAMPD) techniques to explore large molecular and process domains systematically. However, the direct solution of the integrated molecular-process design problem is very challenging as nonlinear interactions between physical properties and process performance render a large proportion of the search space infeasible. We develop a methodology that enables the direct and reliable solution of CAMPD for absorption–desorption processes, using the state-of-the-art SAFT-γ Mie group contribution approach to predict phase and chemical equilibria. We develop new feasibility tests and show them to be highly efficient at reducing the search space, integrating them in an outer-approximation algorithm. The framework is applied to design an aqueous solvent and CO2 chemical absorption–desorption process, with 150 CAMPD instances across three case studies solved successfully. The optimal solvents are more promising than those obtained with sequential molecular design approaches.

Computer‐Aided Molecular and Process Design

Increasing energy prices, tighter environmental regulation, and global competition urge the industry to optimize its processes for converting chemicals and energy. This optimization is far from trivial. Often, the key to major breakthrough relies not only on optimal process conditions but also on selecting suitable molecules as solvents, catalysts, or heat transfer fluids. This selection is highly coupled with the process itself: Choosing the right molecule is a crucial lever for process performance. However, the molecular search space is vast: more than 200 000 000 molecules have already been reported in the CAS registry. The search for the best molecule is thus the search for the needle in the haystack. The ultimate success of a process is only ensured if a molecule is selected based on its optimal process performance. Traditionally, however, the selection of a molecule and the design of the process have been approached sequentially and independently. Computer-aided molecular and process design (CAMPD) methods have been developed to tackle this challenge and systematically tailor molecules for a given application. Thereby, CAMPD can contribute to the transition towards a more sustainable energy and chemical industry, for example, by identifying energy-efficient carbon capture materials, sustainable working fluids for heat pumps, or green solvents for production processes. What is required for a successful application of CAMPD? The basis of a CAMPD problem is a computer-aided molecular design (CAMD) formulation that allows treating the molecular structure as a degree of freedom in an optimization problem. The CAMD formulation is linked with a property model that enables predicting all molecule properties required to evaluate the constraints and objective functions. To reflect the process performance, classical CAMD methods used simplified property-based indicators as the objective function. Recent CAMPD methods integrate detailed process models to assess process performance directly. The recent development of CAMPD/CAMD includes using advanced physically-based and data-driven property models. Moreover, the scope of predicted properties moves beyond the thermodynamic properties to environmental properties such as global warming potential. After decades of CAMPD/CAMD development, these tools have become available for industrial use by implementing CAMPD in flowsheet simulators. Thereby, the effort and required expert knowledge are greatly reduced to set up and solve a CAMPD problem. However, including such new tools in the daily workflow usually takes time. The urge to develop new sustainable processes hopefully will enhance the application of these CAMPD tools. In this special issue of Chemie Ingenieur Technik, authors from industry and academia present their latest developments and applications of CAMPD in energy and chemical engineering. The special issue cannot provide a comprehensive picture of this rapidly developing field. Thus, we aim to provide the reader with an impression of the current status and possible future directions of CAMPD. We hope readers will find inspiration in this special issue and thank all authors for their highly appreciated contributions! Norbert Asprion André Bardow Jonas Mairhofer Johannes Schilling

Development and evaluation of a facile mesh-to-surface tool for customised wheelchair cushions

BackgroundCustom orthoses are becoming more commonly prescribed for upper and lower limbs. They require some form of shape-capture of the body parts they will be in contact with, which generates an STL file that designers prepare for manufacturing. For larger devices such as custom-contoured wheelchair cushions, the STL created during shape-capture can contain hundreds of thousands of tessellations, making them difficult to alter and prepare for manufacturing using mesh-editing software. This study covers the development and testing of a mesh-to-surface workflow in a parametric computer-aided design software using its visual programming language such that STL files of custom wheelchair cushions can be efficiently converted into a parametric single surface.MethodsA volunteer in the clinical space with expertise in computer-aided design aided was interviewed to understand and document the current workflow for creating a single surface from an STL file of a custom wheelchair cushion. To understand the user needs of typical clinical workers with little computer-aided design experience, potential end-users of the process were tasked with completing the workflow and providing feedback during the experience. This feedback was used to automate part of the computer-aided design process using a visual programming tool, creating a new semi-automated workflow for mesh-to-surface translation. Both the original and semi-automated process were then evaluated by nine volunteers with varying levels of computer-aided design experience.ResultsThe semi-automated process showed a 37% reduction in the total number of steps required to convert an STL model to a parametric surface. Regardless of previous computer-aided design experience, volunteers completed the semi-automated workflow 31% faster on average than the manual workflow.ConclusionsThe creation of a semi-automated process for creating a single parametric surface of a custom wheelchair cushion from an STL mesh makes mesh-to-surface conversion more efficient and more user-friendly to all, regardless of computer-aided design experience levels. The steps followed in this study may guide others in the development of their own mesh-to-surface tools in the wheelchair sector, as well as those creating other large custom prosthetic devices.

Techno-economic modeling and assessment of cultivated meat: Impact of production bioreactor scale.

Increases in global meat demands cannot be sustainably met with current methods of livestock farming, which has a substantial impact on greenhouse gas emissions, land use, water consumption, and farm animal welfare. Cultivated meat is a rapidly advancing technology that produces meat products by proliferating and differentiating animal stem cells in large bioreactors, avoiding conventional live-animal farming. While many companies are working in this area, there is a lack of existing infrastructure and experience at commercial scale, resulting in many technical bottlenecks such as scale-up of cell culture and media availability and costs. In this study, we evaluate theoretical cultivated beef production facilities with the goal of envisioning an industry with multiple facilities to produce in total 100,000,000 kg of cultured beef per year or ~0.14% of the annual global beef production. Using the computer-aided process design software, SuperPro Designer®, facilities are modeled to create a comprehensiveanalysis to highlight improvements that can lower the cost of such a production system and allow cultivated meat products to be competitive. Three facility scenarios are presented with different sized production reactors; ~42,000 L stirred tank bioreactor (STR) with a base case cost of goods sold (COGS) of $35/kg, ~211,000 L STR with a COGS of $25/kg, and ~262,000 L airlift reactor (ALR) with a COGS of $17/kg. This study outlines how advances in scaled up bioreactors, alternative bioreactor designs, and decreased media costs are necessary for commercialization of cultured meat products.

Molecule superstructures for computer-aided molecular and process design

A molecular design approach that incorporates the structural information of molecules to unlock property models beyond group contribution methods.