Design Of Industrial Processes Research Articles

A techno-economic study on the co-production of syngas and activated carbon from waste tyre gasification process

Waste tyre gasification offers a variety of benefits amongst which include the production of syngas—an alternate source of energy generation and activated carbon (AC)—a very good adsorbent used in industrial purification processes. In this study, a conceptual design of an industrial production plant design process and economic analysis of waste tyre gasification process for the co-production of syngas and AC were evaluated. Three reactor configurations namely: fluidized bed, fixed bed, and rotary kiln gasifiers were investigated in the design process. The design process put into consideration the total plant cost (TPC), total capital investment (TCI), the cost of raw materials, waste disposal cost, amongst other vital economic parameters. The fixed bed reactor has the highest syngas and AC production with 10,130 kg/h and 214.61 kg/h, respectively when compared to the other gasifiers. The minimum selling price (MSP) of syngas was set as 1$/kg and AC was set at $2/kg. The result obtained shows that the fixed bed production route was the most economical amongst the three reactor configurations considered. The fixed bed route has a net present value (NPV) of 435 M$, return on investment (ROI) of 56%, internal rate of return (IRR) of 54%, and a payback period (PBP) of 4.86 years. Finally, a sensitivity analysis considering a pm 20% variation in key economic parameters such as the syngas MSP, inflation rate, interest rate, tax rate, operating expenditure (OPEX), and capital expenditure (CAPEX) amongst others was investigated. The analysis shows that the syngas MSP, OPEX, inflation rate, and CAPEX have the most effect on the NPV of the waste tyre gasification process.

Enhanced meta‐heuristic methods for industrial winding process modelling

AbstractNonlinear industrial system modelling entails two critical phases: The first is selecting a method in order to estimate the parameter list values, and the second is selecting a proper model structure with a relatively short parameter list. Developing a comprehensive model for an industrial design process is critical for the model‐based control system. This article presents a model‐based strategy that aims to develop three linear and three nonlinear dynamic models using three well‐known meta‐heuristic optimization algorithms to simulate a challenging plant‐wide process. As a case study, an industrial real winding process (WP) is targeted to accomplish the aim of this study. The algorithms have been optimized to find the best weights of the inputs of the WP with a key issue to effectively describe the behaviour aspects of the process. To test the validity of the developed models, a series of experiments were carried out on each of the developed linear and nonlinear models. Several relevant evaluation metric measures are used to demonstrate the models' performance level. The experimental results for training and test sets of 1250 independent samples for each set based upon the proposed modelling schemes show that the mean square error to correctly model the WP occurred in less than 0.001. A comparison of the developed intelligent linear and nonlinear models with the Auto‐Regressive Integrated Moving Average (ARIMA) and Multiple Linear Regression (MLR) models obtained through the evaluation criteria asserts the effectiveness of the proposed models‐based approaches.

Application of Phanerochaete chrysosporium for enhancing gold recovery via bio-oxidation of refractory sulfidic ores in a circumneutral environment

Regardless of the effectiveness of the industrial process design for gold recovery encompassing acidic bio-oxidation and cyanidation, the substantial neutralization of effluents required after bio-oxidation results in a considerable generation of waste streams. Conducting a bio-oxidation at circumneutral pH with in-situ neutralization is a novel technological opportunity for strengthening environmental protection and safety. For the first time, this research reports the capacity of Phanerochaete chrysosporium to oxidize a low-grade refractory gold ore at circumneutral pH. The fungal treatment was evaluated in five culture media regarding pH variation, enzyme activity, and sulfide oxidation. Thereafter, optimal conditions were investigated and then scaled up in a bioreactor. Results indicated that pH > 5.0 decreased the enzyme concentration released by P. chrysosporium, reducing sulfide oxidation. An initial pH of 5.8 led to a 24.4 ± 2.2% sulfide oxidation after 14 days, comparatively better to reported studies in the same pH range. A higher efficiency was attained by replenishing the fungal culture for three cycles, reaching 47.6 ± 2.3% sulfide oxidation and 49.5 ± 2.4% gold recovery. The results were confirmed by UV–visible, C/S detector, SEM and gold fire assay. Overall, this study opens a possibility to explore a bio-oxidation at higher pH, contributing to the vision of a net-zero target.

On noise-induced transient bit flips in subthreshold SRAM

We propose a rigorous SPICE simulation framework, compatible with industrial process design kits, to observe transient bit flips in CMOS SRAM due to the intrinsic transistor noise. The parameters of transient noise simulation are selected according to the noise behaviour and bandwidth of the inverter, however under CPU-time constraint. The methodology is illustrated in 28nm FD-SOI technology. We study the combined effects of the random telegraph noise, flicker and thermal noise sources, for the first time to our knowledge. The extracted mean times to failure (MTTF) are compared to those reported in the literature in extreme voltage, temperature and variability conditions. The MTTF spans from below 0.1ms to 108s, following a theoretical trend logMTTF∝VDD2.

Product modeling design method based on graph neural network and fuzzy inference theory

The method of graph neural network fused with fuzzy inference theory is adopted to conduct in-depth research and analysis on the design of product styling, and designs a method to be used in practical design. Starting from the perspective of quantifying aesthetic preferences, it explores the indicators of objectively quantified preferences and the intelligent design method of product styling under the trend of emotionality and provides a reference experience for optimizing the industrial design process. The product side profile form is deconstructed into 25 sets of planar coordinates, which are used as input data for graph neural network fusion fuzzy inference theory, and the physiological indexes that can represent users' aesthetic preferences are used as output data to build the model and train the network. According to the analysis of the survey data, among the three types of samples of linear type, curved type, and combined type, the percentages of the pictures with the highest degree of preference in the evaluation group reached 68.52%, 75.53%, and 61.11%, respectively, and the weighted scores were higher than those of the control group.

On the crystallization of solid formers during liquefaction of gases

Besides well-known technologies for the liquefaction of air components (N2, Ar, and O2) that of CH4, H2, and CO2 has recently caught attention for the energy transition and climate change targets. Gases undergoing cryogenic processes (cooling, liquefaction, cryo-compression) can contain a certain number of impurities, thus one challenge encountered in liquefaction is the solidification of heavy compounds present in the feed. In dealing with the crystallization risk of solid formers during liquefaction, attention is nowadays addressed to their solubility limits in the liquefied gas at the lowest temperature of the process, because solubility is known to decrease for decreasing temperatures. These limits are then used for tailoring the purification steps upstream the liquefaction train or modifying the operative conditions of the plant to avoid solid formation. In this work, the modeling and the analysis of the available data of several binary mixtures (like H2+N2, N2+CO2, CH4+CO2, and CO2+nC10H22) allow drawing insights about the thermodynamic behavior of such mixtures at low temperatures, showing that the lowest solubility limits are not always encountered at the lowest temperature, and this may have an impact on the design of industrial liquefaction processes. According to the liquefaction pressure, the first risk of solidification of the heaviest component could indeed be related to the deposition from the vapor phase rather than the solidification from the liquid phase. As a matter of fact, solubility limits of a solid former could be lower in a warmer gaseous/supercritical solvent than in a colder liquid solvent, thus solid formation could occur at temperatures that are up to tens of degrees higher than the final liquefaction temperature. Consequently, front-end purification units reducing the content of solid formers in the feed below their solubility limits in the liquefied gas could not be sufficient to completely avoid the risk of crystallization as temperature decreases.

State estimation approach to dual-modal imaging of two-phase flow based on electromagnetic flow tomography and electrical tomography

Monitoring, control and design of industrial processes involving multiphase flows often call for analysis of data from multiple sensors which give information on different quantities of the flowing materials. An example of such case is the problem of monitoring the flow of oil–water mixture: the phase fractions of oil and water, their velocities and volumetric flow rates cannot be retrieved from measurements given by a single sensing/imaging modality. For this reason, multi-modal tomographic imaging systems have been developed. In multi-phase flows, the quantities retrieved from different tomographic instruments are often interconnected—for example, the evolutions of the phase fractions depend on their velocities and vice versa. However, the analysis of data from different tomographic modalities is usually done separately—without taking into account physics that link the quantities of interest. In this paper, we propose a novel approach to image reconstruction in dual-modal tomography of multiphase flows. The governing idea is to combine the two modalities via Bayesian state estimation, that is, we write models that approximate connections between different quantities involved in the process and use sequential measurements from both modalities to jointly estimate these temporally evolving quantities. As an example case, we consider a dual-modal system comprising the electromagnetic flow tomography (EMFT) and electrical tomography (ET). While the EMFT is sensitive to the velocity field but also depends on the phase fractions of fluids, ET measurements are directly linked to phase fractions only. We study the performance of state estimation in EMFT-ET tomography with a set of numerical simulations. The results demonstrate that it outperforms the conventional stationary reconstruction approach, and also provides means for uncertainty quantification in multiphase flow imaging.

Determining and Ordering the Basic Evaluation Criteria in the Furniture Design Process

It is seen that the design-oriented criteria in the furniture product have been analyzed through consumer or user preferences until today. However, the design criteria determined or evaluated through user preferences are not sufficient for the development of products. For this reason, it is necessary to determine the criteria in the design process in the furniture industry from an expert point of view, to determine the importance and weights of these criteria, and to develop standards. In this context, the aim of this study is to determine the criteria and sub-criteria in the furniture design process, and to analyze the importance ratings and weights of these criteria relative to each other. AHP, which is one of the multiple decision-making methods, was applied for the literature review and the analysis of the importance and weights of the criteria and sub-criteria determined by five different experts in the field. A total of 4 main criteria and 25 sub-criteria were determined in order to evaluate the furniture design process with the opinion of experts. Accordingly, the main criterion that has the most importance when evaluating the furniture design process is functionality. This criterion is followed by technical, conceptual and aesthetic criteria, respectively. Planning in accordance with the intended use (functional), material quality (technical), sustainability (conceptual) and form / shape (aesthetic) are the most important sub-criteria under the basic criteria. The findings of the study have the potential to contribute to the objective evaluation of the instructors working in the institutions providing education in the field, to determine the evaluation criteria in national-international design competitions, or to make a joint group decision by multiple decision makers in the sector.

How virtual reality is used in industrial maritime design processes: Two case studies

Virtual reality (VR) is increasingly integrated into maritime design processes, and there is a need to better understand how it can support ship designers in their work. Through mapping and interviews, we investigated how VR was used in two design projects in the maritime industry. We explored two questions: What type of design activities and conversations were facilitated by VR as a collaborative medium? When VR was not selected, what other media were used instead, and for what reasons? We found that despite access to VR, most design conversations were facilitated by emails containing screenshots, visual interpretations, and text annotations. VR was used on a few occasions, together with executable files and flythrough videos made with real-time rendered models generated in a game engine, and a web-based 3D model-sharing tool. The use of VR as a collaboration medium was enabled by a variety of design activities ranging from field studies to 2D sketching and 3D modeling. The cases show how VR needed to be integrated with other forms of communication and was seen as a supplement and not the main communication channel for design. The cases also show that the pipeline required for VR scenes creation enabled other forms of collaboration across different supports, such as web-based online collaboration tools.

The optimal electrode pore size and channel width in electrochemical flow cells

Microfluidic fuel cells, electrolyzers, and redox flow batteries utilize laminar flow channels to provide reactants, remove products and avoid their crossover. These devices often also employ porous flow-through electrodes as they offer a high surface area for the reaction and excellent mass transfer. The geometrical features of these electrodes and flow channels strongly influence energy efficiency. We derive explicit analytical relations for the optimal flow channel width and porous electrode volumetric surface area from the perspective of energy efficiency. These expressions are verified using a two-dimensional tertiary current distribution and porous electrode flow model in COMSOL and are shown to be able to predict optimal parameters in commonly used flow-through and interdigitated flow fields. The obtained analytical models can dramatically shorten modelling time and expedite the industrial design process. The optimal channel width and pore sizes we obtain, in the order of 100 microns and 1 micron respectively, are much smaller than those often used. This shows that there is a significant room for improvement of energy efficiency in flow cells that can sustain the resulting pressure drop.

Mitigation of polyborate precipitation on Pd/Fe2O3 sites during ammonia borane hydrolysis: An alternate insight into the role of oxygen vacancies

Understanding the stability of catalysts is essential for both fundamental science and industrial process design. Herein, we show that oxygen vacancies at the interfaces of Pd/Fe2O3 catalysts prevent the precipitation of polyborate byproducts on the catalyst's surface during ammonia borane (AB) hydrolysis, thereby enhancing the catalyst's stability. Fe2O3-supported Pd nanoparticles were synthesized by a solid-state approach wherein Fe2O3 support size was varied as 20 nm, 45 nm, and 70 nm while the Pd content was maintained at 5% by wt. With increasing cycles, the catalyst containing 20 nm Fe2O3 nanoparticle support is stable, while the catalysts with 45 and 70 nm Fe2O3 supports showed deterioration of catalytic activity. In lower support sizes, due to the fine dispersion of Pd, in-situ oxygen vacancies are created at Pd/Fe2O3 interface during AB hydrolysis. We propose that more water molecules congregate at the vacancy sites, which aids the solubility of polyborates, thereby extending the activity of the catalyst through multiple cycles.

Judging a Socially Assistive Robot by Its Cover: The Effect of Body Structure, Outline, and Color on Users’ Perception

Socially assistive robots (SARs) aim to provide assistance through social interaction. Previous studies contributed to understanding users’ perceptions and preferences regarding existing commercially available SARs. Yet very few studies regarding SARs’ appearance used designated SAR designs, and even fewer evaluated isolated visual qualities (VQs). In this work, we aim to assess the effect of isolated VQs systematically. To achieve this, we first conducted market survey and deconstructed the VQs attributed to SARs. Then, a reconstruction of body structure, outline, and color scheme was done, resulting in the creation of 30 new SAR models that differ in their VQs, allowing us to isolate one character at a time. We used these new designs to evaluate users’ preferences and perceptions in two empirical studies. Our empirical findings link VQs with perceptions of SAR characteristics. These can lead to forming guidelines for the industrial design processes of new SARs to match user expectations.

Design and Optimization of the Training Device for the Employment of Hydraulic Rescue Tools in Traffic Accidents

This paper is concerned with the design and structural optimization of a training device for operators of a hydraulic rescue tool employed during traffic accidents, in conjunction with the improvement of the technical procedures used in such situations. Changes in the design process and subsequent production in the motor industry frequently result in an increased impact resistance of the used structural components. This applies, also, to extrication works and frequently used technical equipment. This paper presents its findings on the design process for the prototype of a training device designed for the extrication cutting drill with the assistance of a hydraulic rescue tool. The primary part of the research was dedicated to structural optimization; therefore, parameter dimensioning of the training device’s prototype was implemented. The device’s mechanical resistance, sturdiness, and stability during the implementation of hydraulic tools were also taken into account. A secondary part of this research comprised experimental results aimed at assessing the time needed to cut through the structural parts of a vehicle—pillars “A” and “B”—while using a hydraulic rescue tool. The structural design of the pillars of selected mid-range vehicles, according to their year of manufacture, was employed. The experiment showed that the newer the vehicle, the higher the cutting resistance of the pillars (predominantly “B”-type pillars). The results revealed that the cutting-work drill contributes to the reduction in the actual cutting time. Furthermore, the identification of the optimal place for cutting and the cutting angle led to more efficient extrication processes that can be applied during rescue works resulting from traffic accidents.

Catalytic conversion of polyoxymethylene with bio-derived substrates: kinetic modeling on solvent enhancement effect and experimental studies on reaction mechanism

Catalytic conversion of waste polyoxymethylene plastics to renewable and value-added chemicals represents a promising area in green chemistry. Previous studies in both academia and industry have focused on thermal depolymerization under harsh operating temperature and pressure. In this work, we have investigated the detailed reaction mechanism for cascade depolymerization and etherification of polyoxymethylene with bio-derived polyols into valuable oxygenates. As one of the highlights in this work, we proposed and validated a two-step mechanism involving depolymerization and nucleophilic attack COC bond. Kinetic modeling, IR and NMR spectra revealed mechanistic information for solvent-enhancement: the synergism of cation (Bi3+), anion (OTf-) and 1,4-dioxane (1) induces formation of intermolecular H bonding thus activating COH bond in polyol molecules, and (2) facilitates nucleophilic attack on carbocation in polyoxymethylene. The outcome of this work will provide useful fundamental data for rational design of industrial processes involving atomic efficient conversion of various polymers into value-added products.

Interdisciplinary design optimization of compressor blades combining low- and high-fidelity models

Multidisciplinary design optimization has great potential to support the turbomachinery development process by improving designs at reduced time and cost. As part of the industrial compressor design process, we seek for a rotor blade geometry that minimizes stresses without impairing the aerodynamic performance. However, the presence of structural mechanics, aerodynamics, and their interdisciplinary coupling poses challenges concerning computational effort and organizational integration. In order to reduce both computation times and the required exchange between disciplinary design teams, we propose an inter- instead of multidisciplinary design optimization approach tailored to the studied optimization problem. This involves a distinction between main and side discipline. The main discipline, structural mechanics, is computed by accurate high-fidelity finite element models. The side discipline, aerodynamics, is represented by efficient low-fidelity models, using Kriging and proper-orthogonal decomposition to approximate constraints and the gas load field as coupling variable. The proposed approach is shown to yield a valid blade design with reasonable computational effort for training the aerodynamic low-fidelity models and significantly reduced optimization times compared to a high-fidelity multidisciplinary design optimization. Especially for expensive side disciplines like aerodynamics, the multi-fidelity interdisciplinary design optimization has the potential to consider the effects of all involved disciplines at little additional cost and organizational complexity, while keeping the focus on the main discipline.

Investigation of the Suppression of Methane Explosions by N2/CO2 Mixtures in Different Proportions.

To characterize the inerting effect of N2/CO2 mixtures containing various proportions on methane-air explosions, a series of experiments were conducted in a 20 L spherical vessel under the normal temperature (25 °C) and normal pressure (101 kPa). Six concentrations (10, 12, 14, 16, 18, and 20%) of N2/CO2 mixtures were selected to analyze the suppression of methane explosion by N2/CO2 mixtures. The results indicated that the maximum explosion pressure (p max) of methane explosions was 0.501 MPa (17% N2 + 3% CO2), 0.487 MPa (14% N2 + 6% CO2), 0.477 MPa (10% N2 + 10% CO2), 0.461 MPa (6% N2 + 14% CO2), and 0.442 MPa (3% N2 + 17% CO2) in the presence of the same N2/CO2 concentration, and similar decreases in the rate of pressure rise, flame propagation velocity, and production of free radicals were observed. Therefore, with the increase of CO2 concentration in the gas mixture, the inerting effect of N2/CO2 was enhanced. Meanwhile, the whole process of the methane combustion reaction was affected by N2/CO2 inerting, which was mainly attributed to heat absorption and dilution of the N2/CO2 mixture. N2/CO2 with a greater inerting effect leads to lower production of free radicals under the same explosion energy and a lower combustion reaction rate at the same flame propagation velocity. The findings of the current research provide references for the design of safe and reliable industrial processes and the mitigation of methane explosions.

Utilization evolving prototype technologies in industrial design in the light of industry 4.0

Utilization evolving prototype technologies in industrial design in the light of industry 4.0

Engaging People Living with Dementia in The Design Process

This study explores how the integration of inclusive design, participatory design (PD), collaborative design, and generative design has led to new methods and tools for involving the elderly in the design process. particularly the elderly with dementia. Dementia is one of the many health issues that become more common among the elderly (though the exact risk factors vary depending on factors like diet, exercise, and genetics). There are approximately 55 million dementia patients globally, with the majority (58%) residing in low- and middle-income nations. Annually, 7.7 million new cases of dementia are diagnosed, and the number of people with dementia is projected to increase to 75,6 million by 2030 and nearly triple to 135.5 million by 2050. In Egypt, there are approximately 600,000 dementia patients, 60% of whom have Alzheimer's, and it is anticipated that by 2030, there will be 1,200,000 dementia patients. Till this day, People living with dementia are still subjected to significant stigmatization. As a result of their exclusion from research and design processes, the majority of newer technologies, products, and services either disregard the needs of older people with dementia or lean more towards the preferences of carers, resulting in designs that are inappropriate or inaccessible to the target population. However, we are currently confronted with significant environmental, social, and cultural obstacles. To be effective, design innovations must be accessible to all stakeholders. We can only use design to solve today's problems by thinking collectively and acting inclusively. By establishing inclusive design as the backbone of the design process and integrating participatory design (PD) techniques, as well as collaborative co-design and generative design research, we are able to better meet the needs of those who will be directly impacted by the final product. People from a wide range of fields need to be brought into the design process. ‘All people are creative and can participate in co-design if they are provided with relevant tools and the appropriate settings for their use.’ Liz Sanders Dementia seniors' inclusion and participation in research and development must therefore be carefully considered. (Specifically for the first three stages of the disease or communicative patients. Therefore, the following research problem arose:• Research Questions: 1-Is it possible for older people who are living with dementia to engage in the design process? 2-How can the role and insights of an industrial designer be utilised to include and involve older people with dementia in research and development, especially in the first three stages of the disease or for patients who are still able to communicate?. Research Significance: The significance of the study lies in the need to allow dementia patients to participate in various stages of the industrial design process while refocusing design efforts on meeting their needs and requirements rather than those expressed on their behalf by others. This prompted industrial designers to create more effective solutions for this elderly population by employing inclusive and co-design strategies. Permitting people with dementia to participate fully in the design process. Research Objectives: The aim of this research is shed light on the application of generative design tools in the context of industrial design processes involving people with dementia. Research Methodology: The research follows the descriptive method by using the investigative method, then the analytical method by gathering and sorting information, and then the deductive method. Research Results & Recommendations:1-It is recommended to use a mix of participatory design (PD) methods, co-design approaches, and generative design techniques to tackle complex design problems that might come up when collaborating with older people who have dementia. 2- The industrial designer must first think about the goal of the ongoing design process and then choose the tools that will facilitate people's thinking and talking about their experiences. 3- Industrial Designers must consider research ethics, safety, and tailoring toolkits to the specific requirements of the design process, as well as selecting materials to cater to participants' (PWD) preferences and providing explanations of how to use the TOOLS

Influence of bubble surface loading on particle-laden bubble rising dynamics in a fluid flow system

Prediction of the rising behaviour of particle-laden bubbles in turbulent flow systems is fundamental to the design and operation of industrial separation processes. However, due to the complexities of such systems, the effect of fluid flow on the rising behaviour of particle-laden bubbles is often ignored. This study examines the combined effect of bubble surface loading (BSL) (particle diameter: 115 μm and 316 μm) and fluid flow on the rising behaviour of a particle-laden bubble (bubble diameter: 2.10 ± 0.08 mm) in a flow system with a pair of counter-rotating vortices, at Reynolds numbers (Re) ranging from 188 to 769. Specifically. the rising trajectory, rise velocity, and aspect ratio of the particle-laden bubbles were determined using the shadowgraphy imaging technique. The results showed that the rise velocity reduces as the BSL increases, reaching a plateau at BSL values > 50%. Over the range of tested conditions, the critical BSL value was appeared to be insensitive to particle size but increased as Re increased. The diminishing bubble surface mobility is believed to be responsible for the observed trend. Further, a drag modification factor as a function of BSL and Reynolds number has been developed. Noticeably, the drag coefficient curves peaked at the corresponding critical BSL values. The drag modification factor may prove to be useful in modelling of the particle separation processes.

Investigation on heat transfer and flow of a sonic steam jet condensation in crossflow of water in pipes

Direct contact condensation is widely used in nuclear reactor thermal-hydraulic systems, underwater propulsion systems, liquid propellant rocket engines and other industrial fields due to its highly efficient heat and mass transfer. Understanding the distribution of the thermal-hydraulic parameters of steam jet condensation systems has become an urgent need for optimal design and safe operation of industrial processes. In this paper, the flow characteristics and heat transfer for the condensation of sonic steam jet in crossflow in a subcooled water pipe are numerically simulated based on experimental results. A two-resistance model under the framework of two-fluid model is employed to consider the mass and heat transfer across the steam-water interface. The steam plume transforms from contraction-cone into expansion-cone when steam mass flux rises from 500 to 900 kg/m2s, and the plume length gradually increases approximately linearly from 2.43de to 4.17de. When the steam mass flux is 900 kg/m2s, the expanding channel of the steam plume allows the jet to accelerate from sonic to supersonic with Ma = 1.43. At the transition of expansion to contraction, the steam dynamic pressure reaches a maximum and the steam total pressure decreases to a minimum. Because the water dynamic pressure is significantly higher than the steam dynamic pressure, the total pressure is maximum at the end of the two-phase region. Mass transfer is much higher in two-phase region than in other regions. The heat transfer coefficient calculated from the interface area decreases from 1.98 to 1.56 MW/m2K, and that calculated from the two-phase region volume increases from 3.37 × 103 to 4.05 × 103 MW/m2K.