Computational Design Tools Research Articles

Compartmentalized CRISPR Reactions (CCR) for High-Throughput Screening of Guide RNA Potency and Specificity.

CRISPR ribonucleoproteins (RNPs) use a variable segment in their guide RNA (gRNA) called a spacer to determine the DNA sequence at which the effector protein will exhibit nuclease activity and generate target-specific genetic mutations. However, nuclease activity with different gRNAs can vary considerably in a spacer sequence-dependent manner that can be difficult to predict. While computational tools are helpful in predicting a CRISPR effector's activity and/or potential for off-target mutagenesis with different gRNAs, individual gRNAs must still be validated in vitro prior to their use. Here, the study presents compartmentalized CRISPR reactions (CCR) for screening large numbers of spacer/target/off-target combinations simultaneously in vitro for both CRISPR effector activity and specificity by confining the complete CRISPR reaction of gRNA transcription, RNP formation, and CRISPR target cleavage within individual water-in-oil microemulsions. With CCR, large numbers of the candidate gRNAs (output by computational design tools) can be immediately validated in parallel, and the study shows that CCR can be used to screen hundreds of thousands of extended gRNA (x-gRNAs) variants that can completely block cleavage at off-target sequences while maintaining high levels of on-target activity. It is expected that CCR can help to streamline the gRNA generation and validation processes for applications in biological and biomedical research.

Sketching Versus Digital Design Tools in Architectural Design

Sketching is a design tool that can be assumed to be ill-structured, does not offer exact solutions, is intuitive, and is open-ended in the initial stages of architectural design. Sketching creates an opportunity for architects to release their creativity and intuition, giving rise to spontaneous ideas and concepts in an organic and natural way. During the initial design phases, like in the conceptual stage of the design, designers receive aid from conventional sketching as their concepts and ideas can easily transform into tangible, real-world forms. With the development of digital design methods like CAD (computer-aided design) in pursuit of AI (artificial intelligence), it has been accepted that manual sketches are no longer the only method used in the design process, and the trend toward using new methods has begun. The diversity and evolution of tools used in architectural design, together with the integration of CAD, AI, and traditional sketching techniques, have contributed to the development of architectural design and facilitated enhanced collaboration, visualization, and efficiency across the design process. As a result, it has evolved to embrace the use of CAD, which was the first method adopted from these developments, as a basic skill in the field of architectural design education. This shift places a strong emphasis on the professional field of architectural design while also encouraging students to explore the innovative potential of CAD for design purposes. CAD presents architects with a robust platform that facilitates the creation of intricate designs and precise measurements during the initial stages of the design process. Following CAD, the development of AI-driven design tools motivates architecture students and designers to transform their concepts into concrete designs. Although it is known that each method mentioned has its own positive or negative aspects, it is not possible to say that any of them is used alone in architectural design processes. At this point, combining the design process with CAD and AI-supported design tools, as well as traditional manual sketching in architecture, helps develop a diverse and adaptable skill set in design. Integrating digital design tools into the architectural field emphasizes the enduring importance of traditional sketches, especially in terms of inspiration and conceptualization in architectural design, while also updating the design process. This document aims to explore the progression of employing diverse design tools, namely manual sketching, CAD, and AI-driven design tools, throughout the architectural design process. This paper undertakes a comparative analysis of using computational design tools instead of traditional sketching with pen and pencil, aiming to juxtapose their respective benefits and drawbacks. In conclusion, although it is not yet possible to assert the superiority of one method over the other, it is evident that traditional sketching continues to hold significant relevance and effectiveness in the design process despite its long-term use.

Enhanced biocatalytic production of cortisol by protein engineering and process engineering

Cortisol, the primary glucocorticoid in humans, plays crucial physiological functions and serves as an intermediate for synthesizing other glucocorticoids. Currently, cortisol production mainly relies on a semi-synthetic route, where the key step of introducing 11β-OH into 11-deoxycortisol is catalyzed by the filamentous fungi Curvularia lunata and Absidia orchidis. This method, however, generates by-products and involves lengthy cultivation. To achieve specific and efficient production of cortisol, we constructed a recombinant biocatalyst by expressing and engineering the human mitochondrial 11β-hydroxylase CYP11B1 in Escherichia coli. Firstly, the balance between CYP11B1 and its redox partners AdR and Adx was regulated through ribosome binding site (RBS) engineering, resulting in a slight increase in cortisol productivity (from 344±19 mg·L−1·d−1 to 407±7 mg·L−1·d−1). Subsequently, the heterologous expression of CYP11B1 was improved through application of the computational design tool PROSS, generating a triple mutant S169V/H354D/L463F with 87.5 % higher cortisol yield than the wild type. Finally, the catalytic performance was improved by optimizing the recombinant protein expression conditions and enhancing the substrate solubility in the reaction system, further elevating the productivity of cortisol to 2.8±0.1 g·L−1·d−1. To our knowledge, this is the highest ever reported cortisol productivity using a human 11β-hydroxylase-based biocatalyst.

Computational Approaches: A New Frontier in Cancer Research.

Cancer is a broad category of disease that can start in virtually any organ or tissue of the body when aberrant cells assault surrounding organs and proliferate uncontrollably. According to the most recent statistics, cancer will be the cause of 10 million deaths worldwide in 2020, accounting for one death out of every six worldwide. The typical approach used in anti-cancer research is highly time-consuming and expensive, and the outcomes are not particularly encouraging. Computational techniques have been employed in anti-cancer research to advance our understanding. Recent years have seen a significant and exceptional impact on anticancer research due to the rapid development of computational tools for novel drug discovery, drug design, genetic studies, genome characterization, cancer imaging and detection, radiotherapy, cancer metabolomics, and novel therapeutic approaches. In this paper, we examined the various subfields of contemporary computational techniques, including molecular docking, artificial intelligence, bioinformatics, virtual screening, and QSAR, and their applications in the study of cancer.

Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar.

Azobenzene-Based Photoswitchable Substrates for Advanced Mechanistic Studies of Model Haloalkane Dehalogenase Enzyme Family.

The engineering of efficient enzymes for large-scale production of industrially relevant compounds is a challenging task. Utilizing rational protein design, which relies on a comprehensive understanding of mechanistic information, holds significant promise for achieving success in this endeavor. Pre-steady-state kinetic measurements, obtained either through fast-mixing techniques or photoswitchable substrates, provide crucial mechanistic insights. The latter approach not only furnishes mechanistic clarity but also affords real-time structural elucidation of reaction intermediates via time-resolved femtosecond crystallography. Unfortunately, only a limited number of such valuable mechanistic probes are available. To address this gap, we applied a multidisciplinary approach, including computational analysis, chemical synthesis, physicochemical property screening, and enzyme kinetics to identify promising candidates for photoswitchable probes. We demonstrate the approach by designing an azobenzene-based photoswitchable substrate tailored for haloalkane dehalogenases, a prototypic class of enzymes pivotal in developing computational tools for rational protein design. The probe was subjected to steady-state and pre-steady-state kinetic analysis, which revealed new insights about the catalytic behavior of the model biocatalysts. We employed laser-triggered Z-to-E azobenzene photoswitching to generate the productive isomer in situ, opening avenues for advanced mechanistic studies using time-resolved femtosecond crystallography. Our results not only pave the way for the mechanistic understanding of this model enzyme family, incorporating both kinetic and structural dimensions, but also propose a systematic approach to the rational design of photoswitchable enzymatic substrates.

Text-to-building: experiments with AI-generated 3D geometry for building design and structure generation

The paper seeks to investigate novel potentials for building design and structure generation that arise at the intersection of computational design and AI-generated 3D geometries. Although the use of AI technologies is exponentially increasing inside the architectural discipline, the design of spatial building configurations using AI-generated 3D geometries is still limited in its applications and represents an ongoing field of investigation in advanced architectural research. In this regard, several questions still need to be answered: how can we design new building typologies from AI-generated 3D geometries? And how can we use these typologies to shape both the real and the virtual world?The paper proposes a new approach to architectural design where artificial intelligence is used as the starting point for design exploration, while computational design procedures are employed to convert AI-generated 3D geometries into building elements – such as columns, beams, horizontal and vertical surfaces. The paper starts with a general overview of the current use of artificial intelligence inside the architectural discipline, and then it moves towards the explanation of specific AI generative models for 3D geometry reconstruction and representation. Subsequently, the proposed working pipeline is analysed in more detail – from the creation of 3D geometries using generative AI models to the conversion of such geometries into building elements that can be further designed and optimised using computational design tools and methods. The results shown in the paper are achieved using Shap-E as the main AI model, though the proposed pipeline can be implemented with multiple AI models. The paper ends by showing some of the generated results, finally adding some considerations to the relationship between human and artificial creativity inside the architectural discipline.The work presented in the paper suggests that the use of computational design tools and methods combined with the tectonics of the latent space opens new opportunities for topological and typological explorations. In a time where traditional architectural typologies are moving towards stagnation due to their inability to satisfy new human needs and ways of living, exploring AI-based working pipelines related to architectural design allows the definition of new design solutions for the generation of new architectural spaces. In doing so, the serendipitous aspect of AI biases is used as an auxiliary force to inform design decisions, promoting the discovery of a new inbuilt dynamism between human and artificial creativity. In a time where AI is everywhere, understanding the measure of such dynamism represents a key aspect for the future of the architectural discipline.

GENTANGLE: integrated computational design of gene entanglements.

The design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased stability. The design of functional overlapping gene pairs is a challenging procedure, and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high-performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user-specified gene pairs. The GENTANGLE source code and its submodules are freely available on GitHub at https://github.com/BiosecSFA/gentangle. The DATANGLE (DATA for genTANGLE) repository contains related data and results and is freely available on GitHub at https://github.com/BiosecSFA/datangle. The GENTANGLE container is freely available on Singularity Cloud Library at https://cloud.sylabs.io/library/khyox/gentangle/gentangle.sif. The GENTANGLE repository wiki (https://github.com/BiosecSFA/gentangle/wiki), website (https://biosecsfa.github.io/gentangle/), and user manual contain detailed instructions on how to use the different components of software and data, including examples and reproducing the results. The code is licensed under the GNU Affero General Public License version 3 (https://www.gnu.org/licenses/agpl.html).

A rule-based framework for capturing geometric characteristics in design: A study of façade analysis for acoustic behaviour in urban space

In urban acoustics, the design of built environment substantially impacts the environmental noise of our everyday lives, as the built environment constantly reflects the sounds of human or non-human actors in its vicinity. The effects produced by these reflected sounds significantly depend on the geometric characteristics of the surrounding building façades. Despite their impact, the façade characteristics are often excluded from urban acoustic simulation models. As a result, sound reflection and scattering that are specifically related to building façades remain largely unexplored in noise control at the urban scale. Inspired by computational design tools used for exploring room acoustics, we investigate how a computational approach enables the analysis of geometric characteristics of façades to simulate urban acoustics during early design processes. This paper introduces a rule-based characterisation framework that enables the representation of geometric façade characteristics and their relationships with acoustic constraints in the form of rules. Our first results showed how these rules allowed for capturing and reconstructing façade geometries based on the given acoustic constraints. We believe that this novel approach empowers designers to describe their initial design ideas in a formalism that can be dynamically adapted to various dimensions, such as urban acoustics, and to reconstruct the form throughout the design process.

A novel framework for set-based steel connection design automation

Existing computational design tools for steel connection design predominantly employ a point-based design (PBD) approach, which requires iterative re-evaluation whenever there are changes in design specifications. This paper introduces a new framework that adopts a set-based design (SBD) approach, aiming to substantially reduce the iteration and time cost associated with steel connection design and rework. The framework integrates a component-set connection design model with a database storage and query-based data retrieval method. The first method enables the flexible and efficient generation of a large connection design space from all possible component combinations, and automated identification of valid connection configurations within it. The latter method allows for automated design space refinement from preference-based evaluation of connection design efficiency and high-speed comparison and selection of optimal connection designs. To evaluate the relative performance of SBD and PBD approaches, the framework is applied to a steel floor system design case study with 62 connections. Results showed that the SBD approach achieved near-instantaneous connection design automation, with a total execution time of fewer than 55 milliseconds, making it over 10 times faster than the corresponding PBD approach.

Building orientation radiation analysis: An early design study using Ladybug

AbstractThe role of building orientation in decreasing energy consumption for cooling purposes was examined in this study. A radiation analysis was performed during the early stage of the architectural design process on a proposed four-story apartment building located in Cebu. The building's performance was evaluated using the Grasshopper Ladybug plugin on a 3D model developed in Rhinoceros. Results indicated that the optimal building orientation that produced the lowest total radiation was situated at 290° from the center of the building, with a recorded value of 731,356 kWh m−2. Conversely, the building orientation that resulted in the highest total radiation was recorded at 210°, with a value of 755,596 kWh m−2. The analysis results were utilized to make informed decisions about building orientation based on environmental factors and surrounding areas. The use of computational design tools in the early stages of architecture design improves the process by enabling designers to optimize building performance and identify potential design issues early, thereby avoiding costly problems.

RE-ENGINEERING OF BUSINESS PROCESSES IN THE DESIGN ACTIVITIES OF MODERN MACHINE-BUILDING ENTERPRISES

Scientific and technical progress, globalization and market competition have faced manufacturers with the fact of a significant reduction in the life cycle of finished products. The modern stage of the development of mechanical engineering is characterized by the wide implementation of the latest achievements of science and technology, which ensures an increase in production efficiency due to the reduction of the length of the design process and the introduction of new, modern types of machines, equipment, materials, etc. Flexible production systems, robots, processing centers appeared, which significantly shortened the production cycle, and in these conditions, new requirements for design activities were formed. In connection with the rapid development of computer technologies, today there is practically no engineering activity that is not equipped with computer modeling and design tools in one way or another. Reengineering is a more radical measure that involves a global restructuring of business processes, therefore, during reengineering, the company's activities can be fundamentally changed. Today, you can find several understandings of the process approach to management. Among them, it is possible to single out an understanding that is based on a systematic consideration of the company's activity as a set of processes and the development of a process management system. This understanding of the process approach is based on the definition of the process and systems approach to the enterprise, the definition of the business process of the enterprise and the system of interrelated processes, as well as the understanding of the steps necessary to implement the process approach. Such an approach is the fundamental and determining point of increasing the efficiency of management, which is the management of production in the direction of its improvement. The peculiarities of design activity and the main approaches to its reengineering are considered.

Investigating the Influence of the Improved Multibody Rope Approach on the Structural Behavior of Dakar Mosque Gridshell Structure

Gridshell structures are characterized by an impressive strength-to-weight ratio, allowing their application in large-span roofing structures. However, their complex construction process and maintenance limited their widespread application. In recent years, the development of parametric and computational design tools has rekindled interest in this type of structure. Among these techniques, the Multibody Rope Approach (MRA) is a form-finding method based on the dynamic equilibrium of a system of masses (nodes) connected by ropes, which allows optimizing the structural shape starting from the dual geometry of the funicular network. To optimize the construction process, an improved version of the MRA, i-MRA, has been recently developed by the authors with the goal of uniforming the size of the structural components. To investigate the impact of the i-MRA method on the structural behavior of gridshell structures, the practical case of the design of a mosque roof is here analyzed. The comparison is carried out in terms of structural performance with respect to permanent and equivalent quasi-static loads. In addition, free-vibration natural-frequency shift is obtained by performing linear modal analysis. Finally, the global behavior with respect to buckling and elastic instability is assessed solving the relevant eigenvalue problem. The results demonstrate that for the roofing of the Dakar mosque, the structural configuration obtained through i-MRA is superior in terms of both construction efficiency and structural performance. The achieved shape exhibits a more uniform distribution of stresses induced by the applied loads together with very limited structural element typologies.

A Computer Design Tool for Ceramic Receivers

Gen3 solar receivers and other components will experience a combination of high temperatures and high stress caused by thermal stress and internal pressure. Under these conditions metallic components, even those manufactured from nickel-based superalloys, have poor reliability. Engineering ceramics could be a solution, as these materials have excellent high temperature strength. However, accurately assessing the reliability of a ceramic component operating in these conditions requires an entirely different approach compared to metallic materials. This paper describes the implementation of statistical models for evaluating the reliability of high temperature ceramic components in srlife – an open-source software package for estimating the life of high temperature concentrating solar power equipment. This new capability allows users to make fair comparisons between competing metallic and ceramic component designs and to accurately assess the plant efficiency and economics of ceramic solar receivers and other components.

Computational design of an efficient and thermostable esterase for polylactic acid depolymerization

A high-performance variant of PLA depolymerase, RPA1511, designated R5, was engineered using combinatorial computational design tools to facilitate closed-loop recycling of PLA waste.

Parametric modeling and fabrication as capturing knowledge: A design computation workflow for historical brick surfaces in Anatolia

Using computational design tools to create meaningful digital representations of architectural heritage delivers both challenges and opportunities. On one hand, digital tools aid the fast and detailed three-dimensional modeling of architectural elements. On the other hand, these models do not sufficiently document the materials and techniques of making. This research proposes a workflow to use computational design tools to analyze historic Anatolian brick elements while integrating their geometry, construction, and part-whole relations in parametric modeling and robotic fabrication processes. Our approach demonstrates a correlation between the design of the surface pattern and material application in historical bricklaying. The proposed workflow can be applied to formalize implicit design knowledge, integrating it into the digital environment and numeric control production codes. This holistic approach to heritage prioritizes both the tangible aspects, such as form and material, and intangible aspects such as the knowledge base of applied techniques.

UDGAN: A new urban design inspiration approach driven by using generative adversarial networks

Abstract The morphological design of urban space affects the quality of the environment. The traditional experience-based design approach was greatly improved by introducing computational design tools. However, the existing urban design tools are mostly developed on pre-set rules or given targets, which have few contributions to enhance creativity or generate inspiring schemes. Therefore, this paper proposes a new computational urban design approach named UDGAN, integrating generative adversarial networks (GANs) and multi-objective optimization algorithms. This model utilizes urban design scheme plans over the past 20 years from a particular designer as training datasets. Four preference models were trained to autonomously generate stylized urban design schemes. Eight morphological parameters were used to analyze the model performance by comparing generated results with the ground truth. This GAN-based surrogate approach is combined with a morphological indicator alignment process using multi-objective optimization model to obtain better results. The result shows that the R2 predicted by the improved Pix2Pix model reaches 0.798, and the similarity of the generated results can be stably distributed between 0.7 and 0.8, so the design scheme of this preferred style can be effectively learned. At the same time, the pre-trained model greatly reduces the time consumption of the design scheme generation, taking 5 min approximately to complete a generation process. This approach quickly generated the design scheme with preferred features, supporting the designer with creativity and greatly saving the time of design creation, transforming computational design into an inspiration-driven process.

COMPUTATIONAL WEARABLES DESIGN: SHOE SOLE MODELING AND PROTOTYPING

Computational wearables design is based on the integration of algorithms into the design process. The use of computational design tools offers a series of advantages in the wearable product design modelling because a complete family of products can be produced with a limited effort from the designer, while at the same time geometries with high complexity can be dealt with a manageable way. The present paper aims to create the appropriate code for modelling shoe soles. The use of a visual programming language leads to a better understanding of the produced code and aims in controlling and optimising the output models. Following the proposed methodology, 3D scanning technologies and plantar pressure diagrams are used for introducing the sole customised geometry, and then the proposed algorithm creates a variety of alternatives of the final shoe sole geometry. As a result, both the customisation and the high number of alternative designs lead to increased creativity and customer satisfaction. Due to the complexity of the geometry produced, 3D printing technologies are incorporated for the prototype implementation.

Quality assessment of residential layout designs generated by relational Generative Adversarial Networks (GANs)

Architectural design, a complex optimization process, employs computational design tools to converge to a subset of design options within a large design space. Recent efforts incorporate deep learning to replace traditional hard-coded rules, yet the nascent and opaque nature of data-driven architectural design requires evaluating its alignment with implicit architectural requirements. This paper assesses whether current data-driven image generation models comply with these non-explicit, domain-specific requirements. Over 80,000 architecturally created floor plans were compared to a similar number of floor plans generated by the authors using the state-of-the-art generative design models. This assessment was based on metrics such as the distribution of space sizes based on their shared/private nature, visibility based on privacy requirements, and room connectivities. The employment of Mann-Whitney U tests and descriptive statistics revealed significant disparities, indicating a gap in the generative design models' understanding of the nuanced, latent rules present in real-world data. These findings highlight the need to develop domain-specific metrics to evaluate the true performance of generative design models, offering insights that will aid in the adoption and advancement of data-driven algorithms in the architecture design domain.

Concept of Computational Fluid Dynamics Design and Analysis Tool for Food Industry: A Bibliometric

Technology that is currently in demand is CFD. By simulating fluid flow around a product on a computer, the computational fluid dynamics (CFD) technique allows designers of new products to be tested. This research aims to analyze the bibliometrics of CFD publications as a design tool in the food industry to determine concepts, trends, and contributions of previous research. Computational Fluid Dynamics (CFD) is a technology used to test product designs through computer simulations of fluid flow around the product. The use of technology in various industries, such as the food industry, is essential to create better products or services. This research uses a bibliometric analysis method supported by theoretical analysis. This research consists of 5 steps, namely (i) determining the research theme for formulating keywords, (ii) collecting publication documents, (iii) data processing, (iv) bibliometric analysis, and (v) preparing a report. The keywords used in this research are "Computational Fluid Dynamics Design (CFD) in Food Industry." The results of the publication search found a total of 211 documents from 1992 to 2023. The average number of publications was 6.59. The trend of CFD publications in the food industry was first carried out in 1992. The development of this publication has been fluctuating, and there has been an increase in publications in the last five years (2019 - 2023). Research publications regarding CFD in the food industry are grouped into 20 subject areas. Contributions to this research consisted of 159 authors, 160 affiliates, and 51 countries. Completing this research will likely provide information regarding publication sources and contributions made by several scientists from various affiliates and countries worldwide.