Design Modeling Research Articles

Predictors of Students’ Proper Waste Disposal Behavior in School Environment: a Partial Least Squares Structural Equation Modeling Approach

It is evident from various reports and statistics that there is a significant gap between the desired environmental state and the current situation, primarily due to improper waste disposal. This study used a predictive-correlational design and structural equation modeling to examine the predictors of proper waste disposal behavior. The research instrument was validated and used to survey 293 high school students across three public schools in Nueva Ecija, Philippines. Using WarpPLS 8.0, the results revealed that (1) accessibility of trash bins, perceived consequences, environmental concern, and perceived behavioral control predict proper waste disposal behavior, and (2) environmental concern and perceived behavioral control sequentially mediate the effect of perceived behavioral control on proper disposal behavior. This study proposes a structural model with meaningful predictive accuracy that can help educational institutions design effective waste management programs empowering education to promote eco-friendly behavior. Future studies may be conducted to test the revised model presented in this study.

A multi-scale homogenization framework for design and strain-gradient modeling of additively manufactured parts fabricated by particulate composites

A multi-scale homogenization framework for design and strain-gradient modeling of additively manufactured parts fabricated by particulate composites

Factorial analysis and modeling of chemical admixtures’ influence on Portland cement paste rheology

The influence of the amount of superplasticizer (SPA) and air-entraining (AEA) admixtures on the rheological properties of a Portland cement paste was investigated based on a statistical approach. The factorial design had the yield stress (YS) and flow as response variables, while the factors of 0.5 ml/kg-cem < SPA < 1.5 ml/kg-cem and 1.2 ml/kg-cem < AEA < 3.6 ml/kg-cem were evaluated, considering main effects, factor interactions, correlation analysis and modelling. The main effects analyses showed that the flow decreased as the AEA or the SPA increased, while the opposite was observed for the YS. The interactions analyses showed that the AEA promoted a reduction trend using the lowest SPA for the flow, but the highest SPA nullified the effect of AEA on flow, which maintained the highest value of 113.7%. Similarly, the AEA favored an increasing trend for the YS due to the interaction with the low SPA content, but a high SPA changed this trend, which decreased to the lowest value of 2652.6 Pa. The flow model (R2 = 84.9%) indicated that the linear effect of the SPA was the most significant, but the linear effect of the AEA and the SPA*AEA interaction were similar in terms of their significance (p-value < 0.001), while the YS model (R2 = 99.6%) showed that the AEA’s linear effect and the AEA*SPA interaction were similar and the most significant (p-value < 0.001). This research provides insights that could facilitate modeling, prediction, and optimization of efficient mixture designs while also gaining clarity considering potential inhibitory effects or synergies, which promotes the responsible consumption and production of construction materials.Graphical

An improved dataset of force fields, electronic and physicochemical descriptors of metabolic substrates

In silico prediction of xenobiotic metabolism is an important strategy to accelerate the drug discovery process, as candidate compounds often fail in clinical phases due to their poor pharmacokinetic profiles. Here we present MetaQM, a dataset of quantum-mechanical (QM) optimized metabolic substrates, including force field parameters, electronic and physicochemical properties. MetaQM comprises 2054 metabolic substrates extracted from the MetaQSAR database. We provide QM-optimized geometries, General Amber Force Field (FF) parameters for all studied molecules, and an extended set of structural and physicochemical descriptors as calculated by DFT and PM7 methods. The generated data can be used in different types of analysis. FF parameters can be applied to perform classical molecular mechanics calculations as exemplified by the validating molecular dynamics simulations reported here. The calculated descriptors can represent input features for developing improved predictive models for metabolism and drug design, as exemplified in this work. Finally, the QM-optimized molecular structures are valuable starting points for both ligand- and structure-based analyses such as pharmacophore mapping and docking simulations.

Multi-response optimization of thermally efficient RC-based geopolymer binder using response surface methodology approach

This research addresses the persistent challenge of strength degradation in geopolymer-based materials incorporating rubber crumb (RC). An optimization model was developed, focusing on critical variables such as RC grade (particle size), percentage incorporation, and the molarity of NaOH, using slags as alumina-silicate precursors. Response surface methodology (RSM) was employed for experimental design and statistical modelling to predict the strengths and thermal conductivity of the resulting geopolymer. The study meticulously analyzed the influence of each parameter on the performance of RC-based geopolymers to understand their practical implications. The models generated were highly significant, demonstrating high practicability and minimal errors. The optimization revealed that a geopolymer with the highest strength (41.91 MPa) and lowest thermal conductivity (0.504 W/mK) can be achieved using a molarity of 10, grade 20 RC, and 18.5% RC content. This study highlights the potential of optimizing RC-based geopolymer mixes to enhance material performance, promoting the sustainable use of waste tires and advancing the development of high-performance construction materials.

Relationship between sintering pressure and leach rate of polycrystalline diamond compacts (PDCs) using central composite design (CCD) modelling

The effect of sintering pressure on the microstructure, wear resistance and leachability of polycrystalline diamond (PDC) was studied using central composite design (CCD) modelling. Pressure and leachability had an inverse relationship due to reduced cobalt pool size and increased diamond contiguity with higher pressures. X-ray diffraction and X-ray fluorescence confirmed the selective removal of cobalt during leaching. The relationship between pressure and leachability was modelled as linear: Y = −1.047× + 11.139, valid within the 5–7 GPa pressure range. For a fixed temperature of 1600 °C, the optimum leach rate was 6.1 μm/h at 5 GPa. This study provided insights into optimizing PDC design and leaching processes for improved performance.

PB-GPT: An innovative GPT-based model for protein backbone generation

With advanced computational methods, it is now feasible to modify or design proteins for specific functions, a process with significant implications for disease treatment and other medical applications. Protein structures and functions are intrinsically linked to their backbones, making the design of these backbones a pivotal aspect of protein engineering. In this study, we focus on the task of unconditionally generating protein backbones. By means of codebook quantization and compression dictionaries, we convert protein backbone structures into a distinctive coded language and propose a GPT-based protein backbone generation model, PB-GPT. To validate the generalization performance of the model, we trained and evaluated the model on both public datasets and small protein datasets. The results demonstrate that our model has the capability to unconditionally generate elaborate, highly realistic protein backbones with structural patterns resembling those of natural proteins, thus showcasing the significant potential of large language models in protein structure design.

Foundry manufacturing of octave-spanning microcombs.

Soliton microcombs provide a chip-based, octave-spanning source for self-referencing and optical metrology. We use a silicon nitride integrated photonics foundry to manufacture 280 single-chip solutions of octave-spanning microcombs on a wafer. By group-velocity dispersion (GVD) engineering with the waveguide cross section, we shape the soliton spectrum for dispersive-wave spectral enhancements at the frequencies for f-2f self-referencing. Moreover, we demonstrate the other considerations, including models for soliton spectrum design, ultra-broadband resonator external coupling, low-loss edge couplers, and the nonlinear self-interactions of few-cycle solitons. To cover the fabrication tolerance, we systematically scan 336 parameter sets of resonator width and radius, ensuring at least one device on each chip can yield an octave-spanning comb with an electronically detectable carrier-envelope offset frequency, which has been supported by our experiment. Our design and testing process permit highly repeatable creation of single-chip solutions of soliton microcombs optimized for pump operation ∼100 mW and high comb mode power for f-2f detection, which is the central component of a compact microsystem for optical metrology.

Automated model order reduction for building thermal load prediction using smart thermostats data

This paper presents a methodology to automatically determine the structure of sufficiently accurate grey-box models for model predictive control, energy efficiency and flexibility applications in buildings. The methodology is based on model reduction and system identification techniques, with a path that enhances data pre-processing, a multistage order reduction, and parameter estimation. The model structure is determined with a cascade approach that either neglects, keeps, or aggregates thermal zones by using discrete and continuous frequency domain techniques. Once the optimal structure is identified, the parameters are calibrated with the measured data from smart thermostats, using the model predictive control relevant identification method. The methodology is applied to a monitored house located in Québec, Canada. The developed algorithm identifies adjacent zones, even when the building layout is unknown, by studying indoor temperature fluctuations. The results concerning the model creation suggest that, for this specific building, the aggregation by floor is the most efficient way for creating reduced order thermal models, limiting uncertainty due to thermal zone interaction. This methodology provides control-oriented models that accurately predict response up to 24-h ahead with Root Mean Square Error less than 0.5 °C and acceptable Fitness Function values for the minimum number of selected parameters. Finally, several scenarios demonstrate the insights gained from using grey-box building thermal models for design, control, and retrofitting applications.

Using machine vision algorithms for characterizing gas-liquid slug flows in vertical pipes

Slug flow, characterized by the distinctive interfacial structures of Taylor bubbles surrounded by liquid films and bridged by aerated liquid slugs, is a dynamically complex two-phase flow pattern exist in many oil and gas, and energy systems. Accurate and precise quantification of such complex flow behaviour is essential for optimal design, safe operation, and reliable modelling of these systems. Existing image-based measurement techniques mostly rely on offline image processing algorithms and are often limited to a narrow set of flow characteristics primarily focusing on Taylor bubbles. Such constraints not only impede real-time flow monitoring and regulation but also leave liquid slug characteristics unmeasured, resulting in an inability to accurately determine the flow characteristics and extract instantaneous void fraction signals. Present study examined the performance of adaptive thresholding (AT) and background subtraction (BS) algorithms in capturing slug flow characteristics. It was found that while the former excels in Taylor bubbles detection and the latter in small bubbles identification, neither individually addresses the accurate measurement of both flow structures' characteristics. This observation, along with the mentioned restrictions of existing algorithms are the main reason for developing the present combined machine vision-based algorithm. While unlocking the ability to extract instantaneous void fraction signals, this new approach facilitates online measurement of a wide range of key flow characteristics, including Taylor bubble length, velocity, void fraction, and surrounding liquid film thickness; liquid slug length and void fraction; and slug unit length, void fraction, and frequency. Parallel to the high-speed imaging, time-series void fraction data was collected using two capacitance sensors installed alongside the imaging area on the pipe, providing benchmark data essential for the validation of the new algorithm's accuracy. The comparisons demonstrated a high degree of accuracy and precision for the combined algorithm. Quantitatively, the new algorithm measured key unit cell characteristics with RMS errors ranging from 2 to 10 %, while the BS and AT algorithms exhibited wider RMS error ranges of 8–46 % and 2–53 %, respectively. This underscores the new algorithm's potential as a transformative tool for slug flow analysis.

Experimentally Calibrated Numerical Modeling for Performance-Based Seismic Design of Low-Frequency Rocking Electrical Cabinets

ABSTRACT In this paper, the performances of two electrical cabinet specimens during shake table tests are described in detail in terms of the observed damage and their measured peak transient responses. The measured responses of the specimens are then used to calibrate simplified numerical models of the two specimens. The calibrated numerical models are used to derive fragility functions to illustrate their usefulness in performance-based seismic design applications. The calibration process and the basic concept of the numerical models can be used for calibrating similar numerical models for other typologies of similar floor anchored non-structural elements that have a rocking failure mode.

Modeling and Analysis of Kamikaze UAV Design with 3 Different Wing Configurations

Appropriate design parameters need to be determined for unmanned aerial vehicles that can perform kamikaze missions. In this study, a UAV with 3 different wing configurations and a fuselage and tail wings were designed, and the flow around the wing was examined using computational fluid mechanics. Advanced modeling techniques were employed to simulate and analyze the aerodynamic behavior of these configurations. The effect of angle of attack (AoA), wing positioning on the fuselage, and wing configurations were investigated. Due to the effect of the wing sweep angle, high-pressure values in the arrow-angle wing were lower than in rectangular and trapezoidal wings. In a similar situation, the flow separation on the arrow-angle wing is less advanced towards the wing tip. When the wing type and connection location were examined, the highest ${{C}_{l}}/{{C}_{d}}$ ratio was obtained in the trapezoidal model connected to the fuselage in the middle. The results of numerical wing models compared with the theoretical lift coefficient were consistent. Trapezoidal and rectangular wings had a high lift coefficient, but after ${{15}^{\circ }}$ of AoA, the lift coefficient decreased. At angles of attack beyond ${{15}^{\circ }}$, the arrow-angle wing still has an increasing lift coefficient. As the angle of attack increased, the drag coefficient was also enhanced. The lowest drag coefficient occurred in the arrow-angle wing model. Up to ${{5}^{\circ }}$of AoA, all wing models raised the ${{C}_{l}}/{{C}_{d}}$ ratio. The ${{C}_{l}}/{{C}_{d}}$ ratio decreased at higher angles of attack. As a result of the examination, it would be more correct to choose trapezoidal and arrow-angle wings.

Indoor space thermal cycle design and animation 3D modeling based on digital light processing technology

With the continuous development of architectural design concepts, the thermal cycle optimization of interior space has become an important topic to improve energy efficiency and comfort. The introduction of digital light processing (DLP) technology provides new possibilities for 3D modeling and thermal cycle analysis. This study uses digital light processing technology to design and optimize the thermal cycle of indoor space, and explores its application in real-time animation 3D modeling to provide a more intuitive visual display. DLP technology is used to build a three-dimensional model of interior space, and heat flow analysis software is combined to simulate the thermal cycle of different design schemes. The dynamic simulation method was used to analyze the change of heat circulation in the exhibition room and its influence on the indoor environment. The results show that the indoor thermal cycle optimized by DLP technology can effectively improve the heat distribution uniformity and energy efficiency utilization, and the simulation results show that the improved scheme has significant advantages in thermal comfort. This study proves the feasibility and effectiveness of digital light processing technology in indoor space thermal cycle design, and provides a new idea for future architectural design and thermal cycle management.

Nutrition Design Modeling Method Development for Adana Origin Maize Starch Granules by Structural and Elemental Analysis

The granules of Adana origin maize starch were treated with thermal, acidic and amylase enzyme degradation processes and examined using the Field Emission Gun – Scanning Electron Microscope (FEG-SEM) to determine the structure analysis and composition modeling. The morphology deformation of the starch granules in shape, surface and size, and elemental analysis peaks and data were determined upon degradation. The microstructure images resulted the occurrence of stretches and slit cracks on the nanoparticle surface and high carbohydrate carbon elemental compound. The degraded amylopectin layers upon the conversion stages were notably presented with high clarity ever published. Investigation of the treated starch granules presented that the granules presented an explicit swelled, splintered and spherical granules model, and a high carbon carbohydrate nutrition model. The swelling and gelling existence temperature of the starch samples were detected as 69 °C.

Analysis and Topology Optimization of Chain Sprocket in ANSYS Workbench

This paper aims to develop an optimized driven sprocket, focusing on the driving sprocket of the KTM 390. The process begins with the creation of the driving sprocket model in SolidWorks 2022. Subsequently, finite element modelling and analysis of the initial design are conducted using ANSYS Workbench software, simulating the strength, safety factor, and lifespan of the model. The next step involves topologically optimizing the model, with the goal of achieving a 36% reduction in sprocket mass without compromising its performance. Finally, design validation is performed on the optimized model, followed by a reassessment through static analysis to ensure the reliability of the results. Keywords: optimized driven sprocket, KTM 390, SolidWorks 2022, ANSYS Workbench, simulation, safety, chain sprocket

Investigation of Delamination Characteristics in 3D-Printed Hybrid Curved Composite Beams.

This study focuses on understanding the impact of different material compositions and printing parameters on the structural integrity of hybrid curved composite beams. Using the continuous filament fabrication technique, which is an advanced fused deposition modelling process, composite curved beams made of short carbon and various continuous fibre-reinforced nylon laminae were fabricated and subjected to four-point bending tests to assess their delamination characteristics. The results show that the presence of five flat zones in the curved region of a curved beam achieves 10% and 6% increases in maximum load and delamination strength, respectively, against a smooth curved region. The delamination response of a curved composite beam design consisting of unidirectional carbon/nylon laminae is superior to that of a curved beam made of glass fibre/nylon laminae, while the existence of highly strengthened glass fibre bundles is alternatively quite competitive. Doubling the number of continuous fibre-reinforced laminae results in an increase of up to 36% in strength by achieving a total increase in the beam thickness of 50%, although increases in mass and material cost are serious concerns. The hybrid curved beam design has a decrease in the maximum load and the strength by 11% and 13%, respectively, when compared with a non-hybrid design, which consists of some type of stronger and stiffer nylon laminae instead of short carbon fibre-reinforced conventional nylon laminae. Two-dimensional surface-based cohesive finite element models, which have a good agreement with experimental results, were also established for searching for the availability of useful virtual testing. The results from this study will greatly contribute to the design and numerical modelling of additively manufactured hybrid composite curved beams, brackets, and fittings.

Novel monastrol/melatonin hybrids as a new approach for colorectal cancer intervention: design, synthesis, biological activity, and drug-likeness modeling studies

Considering the important increase in the incidence and mortality of colorectal cancer, it is necessary to develop new strategies in the search for new alternatives against this disease. Hence, we designed and synthesized a new series of monastrol/melatonin hybrids and evaluated them in vitro and in silico to determine the potential of these new chemical entities on this type of cancer. To achieve this goal, the different compounds were evaluated in human colorectal adenocarcinoma cells SW480, while establishing the selective potential of the hybrids through the nonmalignant human colon mucosal epithelial cell line (NCM460). According to the results, hybrids 6a, 6c, 6i, and 6j displayed the best response, with IC50 values in the range of 5.2 and 6.3 μM, inducing important changes depending on concentration and time. In addition, these compounds were extremely active in comparison to the single molecules, and they were slightly more selective than the reference drug (5 fluorouracil, 5-FU). Besides, an optimal pharmacokinetic and toxicological profile was also estimated for hybrids 6a, 6c, 6i, and 6j. Altogether, novel hybrids of monastrol-MLT, in particular, 6a (-H), 6c (3-OMe), 6i (3,4-OMe), and 6j (3,5-OMe) could be addressed as starting points for further pharmacological studies concerning to combat colorectal cancer.

Sistem Informasi Bimbingan Tugas Akhir Mahasiswa menggunakan Model SDLC Berbasis Iconix Process

The final thesis assignment plays a crucial role in enabling students to meet the graduation requirements from college. However, the process of scheduling guidance for the final assignment between students and lecturers still relies on several common applications such as WhatsApp or email, which are not specifically designed for this purpose. The accumulation of incoming messages and various types of message information poses a challenge in the guidance process, leading to missed messages between students and lecturers and a lack of recorded information regarding the history of the process and guidance materials. These are some of the current issues. This paper aims to evaluate the functionality, quality, and reliability of the system by conducting black box testing on the application developed for the student final project guidance information system. This application uses the Iconix process-based SDLC (system development life cycle) model, covering student and lecturer profile information, guidance information, proposal submission, progress of the final thesis assignment, meeting schedule, guidance material, discussion forum, survey evaluation, and contact information. The SDLC model is employed in this research because it can effectively and efficiently achieve project targets, enhance software quality standards, and assist in better risk management and adaptation to change. The model comprises planning, needs analysis, design using the Iconix process, implementation, system testing, and maintenance. The Iconix process is utilized for system design modeling and analysis. Black box testing is performed on the system to verify that the system’s functional requirements are operating correctly. The findings of this research can serve as a control for management in the service and administration of final assignment guidance in higher education.

Regulation of Rubisco activity by interaction with chloroplast metabolites.

Rubisco activity is highly regulated and frequently limits carbon assimilation in crop plants. In the chloroplast, various metabolites can inhibit or modulate Rubisco activity by binding to its catalytic or allosteric sites, but this regulation is complex and still poorly understood. Using rice Rubisco, we characterised the impact of various chloroplast metabolites which could interact with Rubisco and modulate its activity, including photorespiratory intermediates, carbohydrates, amino acids; as well as specific sugar-phosphates known to inhibit Rubisco activity - CABP (2-carboxy-d-arabinitol 1,5-bisphosphate) and CA1P (2-carboxy-d-arabinitol 1-phosphate) through in vitro enzymatic assays and molecular docking analysis. Most metabolites did not directly affect Rubisco in vitro activity under both saturating and limiting concentrations of Rubisco substrates, CO2 and RuBP (ribulose-1,5-bisphosphate). As expected, Rubisco activity was strongly inhibited in the presence of CABP and CA1P. High physiologically relevant concentrations of the carboxylation product 3-PGA (3-phosphoglyceric acid) decreased Rubisco activity by up to 30%. High concentrations of the photosynthetically derived hexose phosphates fructose 6-phosphate (F6P) and glucose 6-phosphate (G6P) slightly reduced Rubisco activity under limiting CO2 and RuBP concentrations. Biochemical measurements of the apparent Vmax and Km for CO2 and RuBP (at atmospheric O2 concentration) and docking interactions analysis suggest that CABP/CA1P and 3-PGA inhibit Rubisco activity by binding tightly and loosely, respectively, to its catalytic sites (i.e. competing with the substrate RuBP). These findings will aid the design and biochemical modelling of new strategies to improve the regulation of Rubisco activity and enhance the efficiency and sustainability of carbon assimilation in rice.

Exploring the relationship between embedment behaviour in cross-laminated timber and its layers: An experimental study

Cross-laminated timber (CLT) has become popular as a construction material and the design of CLT connections is typically based on empirical equations with an average embedment strength of the wood-based product. The experimental study presented herein aims at enhancing the understanding of the relationship between the CLT embedment behaviour and the single layers it is composed of. Non-linear embedment stress–displacement relationships were measured in 244 full-hole and half-hole embedment tests on structural timber boards as well as on CLT produced of parts of the same boards. Three different fasteners, namely a steel dowel with a diameter of 12 mm and the threaded part of screws with a nominal diameter of 6.5 mm and 10 mm, were studied. The design of the experiments allowed to validate a simple mechanical model with parallel springs for the CLT, which showed good agreement with experiments. In addition to a validation of the non-linear spring model, this unique experimental data-set is further exploited in a comparison with empirical equations and for the derivation of a non-linear embedment ratio, between parallel and perpendicular to the grain embedment stresses, over the displacement. Knowledge of the relationship between the non-linear embedment behaviour of the single layers and the CLT element can be further exploited in the engineering design and numerical modelling of CLT connections with dowel-type fasteners.