Variety Of Designs Research Articles

SIMPLIFIED METHOD FOR ESTIMATING A DYNAMIC LOADRATING FOR ROLLING BEARINGS

The method for calculating the dynamic load ratings of rolling bearings is described in the ISO 281 standard.The calculation procedure presented there requires reading appropriate values from many tables, dependingon the geometry of the bearing components. This approach makes numerical calculations and quick estimationof the dynamic load ratings for various bearing design variants difficult. Moreover, the tables are discrete(they provide selected values, e.g. for nominal bearing contact angles every 15), and intermediate values,in accordance with the commentary included in the ISO 281 standard, should be calculated using linearinterpolation. However, in reality, the parameters given in the tables are not linearly dependent on each other,which makes this interpolation inaccurate. In the context of the mentioned imperfections of the ISO 281standard, the aim of the work is to simplify the calculation procedure, adapt it to numerical applications,and replace linear interpolation with an appropriate non-linear function. The difference between the valuescalculated according to the proposed formula and the value calculated according to the ISO 281 standard is onaverage less than 0.5%.

Exploring the interaction of design variability and stochastic operational uncertainties in software-intensive systems through the lens of modeling

AbstractIn software-intensive systems, navigating the complexities that emerge from the interaction of design variability and stochastic operational uncertainties presents a daunting challenge. This paper delves into the dynamics between these two dimensions of uncertainty, offering novel insights about how modeling can contribute to the analysis of their combined impact upon system properties. By elevating the abstraction level at which probabilistic models are conceptualized, our approach enables an integrated analysis framework that considers both structural and quantitative dimensions of design spaces. Through the introduction of novel language constructs, our methodology facilitates the direct referencing of structural relationships within probabilistic behavioral specifications. Furthermore, the adoption of novel quantifiers in probabilistic temporal logic enables evaluating complex properties across diverse design variants, thereby streamlining the assessment of guarantees within the solution space. We demonstrate the feasibility of this approach on four case studies, showcasing its potential to offer comprehensive insights into the trade-offs and decision-making processes inherent in managing different types of structural design variability and operational uncertainties in software-intensive systems.

Event-related potentials in studies of the implicit component of cognitive biases

The review analyzes neurophysiological correlates of the implicit component of cognitive bias in the processes of perception and decision-making. The review identifies the leading methodological pipeline for analysis of the implicit component of cognitive bias, and justifies its choice in terms of the objectives of this review. The method of recording event-related potentials (ERPs) was chosen as the main approach to determining neurophysiological indicators of implicit processes. The analysis of literature allowed us to identify ERP components reproduced in the works of different authors using different variants of experimental designs for studying implicit bias, which may indicate the presence of common neurophysiological mechanisms associated with implicit processes in cognitive bias. The possibility of using other approaches to the analysis of EEG data to obtain new information about the mechanisms of implicit components in cognitive bias is also discussed.

"Mirror, mirror in the call": Exploring the Ambivalent Nature of the Self-view in Video Meeting Systems with Self-Reported & Eye-Tracking Data

Video meeting systems offer great potential for work and life, but they can also have negative effects. One reason is the presence of technical stimuli that do not exist in the physical world. A prominent example is the self-view feature, a mirrored image of oneself shown during the video meeting. The self-view feature comes with a trade-off between the advantage of enhancing control and the disadvantage of increasing cognitive load of its users. So far, research is scarce when it comes to understanding this ambivalent nature and studies mostly relied on self-reported data without considering the actual interaction with the self-view. To address this gap, we conducted an experimental study with 57 participants and two design variants (with/without self-view), analyzed user perceptions through surveys and interviews, and explored gaze patterns using eye-tracking technology. Results reveal varying perceptions of cognitive load and control among self-view users and between the design variants, highlighting its ambivalent nature. We see differences in how participants interact with the self-view. In a cluster analysis, we identify three user groups (Benefiting Users, Cognitively Challenged Users, Control Losing Users). These groups also show differences in visual behavior, especially median fixation duration, and user characteristics. Based on our findings, we outline design recommendations for more flexible and intelligent design solutions by considering user groups and their individual differences.

ViralPrimer: a Web Server to Monitor Viral Nucleic Acid Amplification Tests' Primer Efficiency during Pandemics, with Emphasis on SARS-CoV-2 and Mpox.

Accurate pathogen identification is crucial during outbreaks, especially with the emergence of new variants requiring frequent primer updates. However, resources for maintaining up-to-date verification of primer sequences are often limited, which poses challenges for reliable diagnosis and hinders potential monitoring efforts based on genome sequencing. To address this, we introduce ViralPrimer, a web server facilitating primer design, SARS-CoV-2 and Mpox variant monitoring, and adaptation to future threats. ViralPrimer aims to enhance diagnostic accuracy with its comprehensive primer database, mutation analysis assistance, and user primer upload feature. Its adaptable design allows monitoring of other rapidly mutating pathogens, contributing to broader public health protection efforts. ViralPrimer is freely accessible and open to all users with no login requirement at https://viralprimer.elte.hu/. The application is hosted on a DJANGO v3.2.13 web server, with a PostgreSQL database, and the frontend was implemented using jQuery v3.6.0, vanilla JavaScript vES6, and Bootstrap v5.1. https://viralprimer.elte.hu/help#downloads.

Dirichlet latent modelling enables effective learning and sampling of the functional protein design space

Engineering proteins with desired functions and biochemical properties is pivotal for biotechnology and drug discovery. While computational methods based on evolutionary information are reducing the experimental burden by designing targeted libraries of functional variants, they still have a low success rate when the desired protein has few or very remote homologous sequences. Here we propose an autoregressive model, called Temporal Dirichlet Variational Autoencoder (TDVAE), which exploits the mathematical properties of the Dirichlet distribution and temporal convolution to efficiently learn high-order information from a functionally related, possibly remotely similar, set of sequences. TDVAE is highly accurate in predicting the effects of amino acid mutations, while being significantly 90% smaller than the other state-of-the-art models. We then use TDVAE to design variants of the human alpha galactosidase enzymes as potential treatment for Fabry disease. Our model builds a library of diverse variants which retain sequence, biochemical and structural properties of the wildtype protein, suggesting they could be suitable for enzyme replacement therapy. Taken together, our results show the importance of accurate sequence modelling and the potential of autoregressive models as protein engineering and analysis tools.

Expanding the biosynthesis spectrum of hydroxy fatty acids: unleashing the potential of novel bacterial fatty acid hydratases

BackgroundHydroxy fatty acids represent an emerging class of compounds with promising applications in the chemical, medicinal and functional food sectors. The challenges associated with their chemical synthesis have spurred exploration of biological synthesis as an alternative route, particularly through the use of fatty acid hydratases. Fatty acid hydratases catalyse the regioselective addition of a hydrogen atom and a hydroxyl group from a water molecule to the carbon–carbon cis-double bond of unsaturated fatty acids to form hydroxy fatty acids. Despite having been discovered in the early 1960s, previous research has primarily focused on characterizing single fatty acid hydratase variants with a limited range of substrates. Comprehensive studies that systematically examine and compare the characteristics of multiple variants of fatty acid hydratases are still lacking.ResultsIn this study, we employed an integrated bioinformatics workflow to identify 23 fatty acid hydratases and characterized their activities against nine unsaturated fatty acid substrates using whole-cell biotransformation assays. Additionally, we tested a dual-protein system involving two fatty acid hydratases of distinct regioselectivity and demonstrated its suitability in enhancing the biosynthesis of di-hydroxy fatty acids.ConclusionsOur study demonstrates that fatty acid hydratases can be classified into three subtypes based on their regioselectivity and provides insights into their preferred substrate structures. These understandings pave ways for the design of optimal fatty acid hydratase variants and bioprocesses for the cost-efficient biosynthesis of hydroxy fatty acids.

Discourse complex <i>i da</i> ‘and yes’ as a dialogue actualizer in modern Russian speech

The article examines semantic and pragmatic features of the discursive complex i da (“and yes”). The relevance of the research is explained by the active inclusion of i da in contemporary speech practice, various genres and styles over the past decade, which was not observed before. The novelty of the research lies in the fact that the element i da becomes the object of linguistic analysis for the first time. This study contributes to the understanding of the discursive complex i da in the context of modern linguistic practices. The findings of this research can be beneficial for further linguistic studies and practical applications. The element i da is not recorded in dictionaries and reference books, which also testifies to the novelty of the material presented in the article, which was extracted from the “National Corpus of the Russian Language”, the electronic media bank “Integrum”. The paper is also based to some degree on the personal observations of the authors. This study provides a fresh perspective on the linguistic element i da, contributing to the existing body of linguistic research. The research was conducted within the framework of the structural and descriptive method using semantic, syntactic, and contextual analysis. As a result, the main discursive role of the complex i da was established, i. e., maintaining the interactive nature of conversation through a ‘delayed response’ mechanism, which allows considering i da as a feedback marker. The discursive complex i da involves a real or potential (in the case of a monologue) interlocutor/opponent in the discourse, performing the role of a dialogic actualizer. The core seme of the complex (‘agreement’) can be explicitly supported by the context, and the addressee of the agreement can be not only the ‘other’ but also the speaker himself. The study reveals the rhetorical potential of i da in monologic speech. This research provides a comprehensive analysis of the discursive complex i da, highlighting its role in dialogic actualization and its rhetorical potential in monologic speech. The variants of punctuation design of the complex i da identified during the research indicate the need for its further study and the creation of a theoretical basis for subsequent codification in punctuation guides. The study proposes a hypothesis about the appearance of i da in Russian as a result of calquing English phrases and yes / and yeah, which are of international nature. This research emphasizes the importance of further investigation into the discursive complex i da, its punctuation variants, and its origins in the Russian language.

Structures of the Foamy virus fusion protein reveal an unexpected link with the F protein of paramyxo- and pneumoviruses.

Foamy viruses (FVs) constitute a subfamily of retroviruses. Their envelope (Env) glycoprotein drives the merger of viral and cellular membranes during entry into cells. The only available structures of retroviral Envs are those from human and simian immunodeficiency viruses from the subfamily of orthoretroviruses, which are only distantly related to the FVs. We report the cryo-electron microscopy structures of the FV Env ectodomain in the pre- and post-fusion states, which unexpectedly demonstrate structural similarity with the fusion protein (F) of paramyxo- and pneumoviruses, implying an evolutionary link between the viral fusogens. We describe the structural features that are unique to the FV Env and propose a mechanistic model for its conformational change, highlighting how the interplay of its structural elements could drive membrane fusion and viral entry. The structural knowledge on the FV Env now provides a framework for functional investigations, which can benefit the design of FV Env variants with improved features for use as gene therapy vectors.

Machine learning-assisted amidase-catalytic enantioselectivity prediction and rational design of variants for improving enantioselectivity

Biocatalysis is an attractive approach for the synthesis of chiral pharmaceuticals and fine chemicals, but assessing and/or improving the enantioselectivity of biocatalyst towards target substrates is often time and resource intensive. Although machine learning has been used to reveal the underlying relationship between protein sequences and biocatalytic enantioselectivity, the establishment of substrate fitness space is usually disregarded by chemists and is still a challenge. Using 240 datasets collected in our previous works, we adopt chemistry and geometry descriptors and build random forest classification models for predicting the enantioselectivity of amidase towards new substrates. We further propose a heuristic strategy based on these models, by which the rational protein engineering can be efficiently performed to synthesize chiral compounds with higher ee values, and the optimized variant results in a 53-fold higher E-value comparing to the wild-type amidase. This data-driven methodology is expected to broaden the application of machine learning in biocatalysis research.

Ski S. V. Influence of gamma irradiation on the reverse current-voltage characteristics of silicon photomultipliers

The study investigated the effect of Co60 gamma-quanta on the reverse current-voltage characteristic (IV) of silicon photomultiplier (SiPMs) with 1004 cells, which themselves were optically isolated from each other n+ –p–p+ -structures. The cells were optically isolated from each other by trenches filled with tungsten after passivation of the walls with SiO2 and Si3N4 layers. Two variants of structural design of SiPMs were studied. Two variants were tested for the trench metal connection in the SiPMs: variant BI connected the trench metal to the n+-region of the cell through a quenching polysilicon resistor, while variant BII connected it to the p+-region. The breakdown voltage of the investigated SiPMs was Ubr = 34 ± 1.0 V. The samples were irradiated in both the active electrical mode (avalanche breakdown mode) and the passive mode (reverse bias Ub = 0 V). It was discovered, that at dose of D = 106 rad, the dark current for SiPM (BI) and (BII) increased by 6–7 times when irradiated in passive mode and by 15–16 times for SiPM (BII) when irradiated in active mode. For SiPM (BI) irradiated in the avalanche breakdown mode, the dark current increased by 104 times at D = 105 rad. The research demonstrates that the radiation-induced degradation of the dark current in the SiPMs under study is due to an increase in the generation and, primarily, surface components. This is a result of the accumulation of positive charge in the insulating layer of the separating trenches.

B-124 Structure-based Variant Effect Prediction and Design of Functional CYP2C9 Variants by Virtual Evolution

Abstract Background The decryption of massive variants of uncertain significance (VUS) discovered by sequencing poses the main challenge in the post-sequencing era. VUS also resulted in a particular problem in the field of pharmacogenomics, which can be epitomized by drug-metabolizing enzymes, such as CYP2C9. Therefore, an accurate model that incorporates the inner connection between massive protein variants and their function alterations is crucial for clinical annotation of human variome and the virtual evolution of enzyme engineering for biotherapeutics. Methods We developed a model named variant effect recognition network for CYP2C9 (vERnet-P), which learned features from AlphaFold2-predicted protein structures and predicted the enzyme activity of missense single-nucleotide variants in CYP2C9. The two crucial strategies of vERnet-P are the construction of amino acid interaction networks and the application of deep learning. Therefore, vERnet-P leveraged highly accurate protein structures predicted by AlphaFold2, combined with novel techniques for enriching and capturing useful information. Based on the accurate and preemptive prediction of CYP2C9 variants, we performed the saturation mutation prediction on several sites of CYP2C9 to identify new variants with the expected function. Furthermore, the drug metabolic activities of these newly identified variants were investigated with two probe drugs by in vitro metabolic activity assessments. Results An accuracy of up to 93.5% for the classification of activity levels was yielded in the testing dataset. In addition, the tasks for recognizing the high-activity and low-activity variants both achieved 93.5% accuracies, demonstrating that vERnet-P truly learned the features related to enzyme activity, rather than the selection bias to one kind of samples. Strikingly, the AUC values of the ROC and the PR reached 0.971 and 0.966 respectively in the testing cohort for vERnet-P. vERnet-P achieved the strongest agreement with massively parallel assessments relative to the other 8 computational variant effect predictors in the task of predicting CYP2C9 variant enzyme activity. We explored 6 mutant sites in CYP2C9 by using vERnet-P to perform saturation mutation prediction and found 12 novel variants with a high possibility of activity changing. We identified 6 variants with most likely increased activity by using the prediction of wild-type as a cutoff, consequently, 6 variants with most likely decreased activity were selected. According to these 12 discovered variants, 10 were strongly confirmed by the in vitro metabolic activity assays of both probe drugs. Conclusions vERnet-P achieved state-of-the-art performance in predicting the CYP2C9 variant enzyme activity. The preemptive prediction for CYP2C9 variants can efficiently provide the clinical drug dosing guideline. Furthermore, by saturating mutation prediction on several sites, our results indicated the evolutionary direction of CYP2C9 enzyme activity and discovered some brand-new CYP2C9 variants with ultra-strong functional alterations, which have not previously been reported. The results of in vitro metabolic activity assessment were highly consistent with our in silico prediction, indicating the potential of AI models for inferring evolutionary direction and designing novel variants with the expected function.

Leveraging HLS to Design a Versatile & High-Performance Classic McEliece Accelerator

By harnessing fundamental quantum properties, a large-scale quantum computer could undermine currently deployed public-key algorithms. The post-quantum, code-based cryptosystem Classic McEliece (CM) addresses this security concern. However, its large public key size (up to 1.3MB) poses various hardware implementation challenges. In this paper, we focus on the high memory bandwidth requirements of the CM encoding function, in the context of heterogeneous CPU-FPGA devices. More concretely, we target the acceleration of public-key loading and processing from any globally-shared or accelerator-private memory system. We present a novel and constant-time accelerator eEnc that exploits the elevated parallelization potential of FPGA devices to yield high-performance results. Our accelerator implements the encoding and the random error vector generation functions, which comprise the main computational load of Encapsulation. Two accelerator design variants are introduced, providing different hardware tradeoffs. Regarding intra-accelerator data communication, and unlike other state-of-the-art (SOTA) works, we combine a streaming protocol with task-level parallelization to remove the need to store the public key in accelerator-private memories. Our proposed design shows new record execution times over its SOTA counterparts, ranging on average from 3.5 × up to 7.7 × across the five security level parameter sets. Our end-to-end implementation in a Zynq SoC shows an average speedup of 2.2 × compared to a 64-bit vectorized CM software-baseline. The elevated logic resource consumption, characteristic of HLS designs, can be readily adjusted with a performance tradeoff.

Design of sustainable integrated energy systems for green ports – selection and sizing

Abstract Design of sustainable and integrated energy systems for marine port is a complex problem, involving multiple conflicting objectives like energy efficiency and minimum losses, cost-effectiveness, and avoiding excessive cycling and degradation. This paper addresses the sizing of integrated and sustainable port energy systems with renewable energy sources and energy storage systems based on two different methods. Both developed methods start by selecting design sets representing the gradual expansion of renewable sources and storage to the maximum size, limited by various constraints. Each design variant is evaluated based on the energy demands of the port, historical prices, and site energy production capacity. The first method, developed by ITK Engineering GmbH, uses a conventional deterministic forecasting approach with detailed annual data. The latter, developed by NTNU, employs several 24-hour data sets to capture annual energy dynamics. Key performance indicators for both methods are defined based on the total cost, with the benchmark cost obtained using the first (deterministic) method with 100% grid-supplied energy. Two virtual ports of different sizes (Port A and B) are established in two electric markets (1 and 2) for verification and benchmarking. The paper then discusses the influence of uncertainty in 24-hour data sets, used by the second (stochastic) method, for all cases.

Manufacturing of breathable, washable, and fabric-integrated squid skin-inspired thermoregulatory materials.

Advanced thermal management technologies represent an important research frontier because such materials and systems show promise for enhancing personal physiological comfort and reducing building energy consumption. These technologies typically offer the advantages of excellent portability, user-friendly tunability, energy efficiency, and straightforward manufacturability, but they frequently suffer from critical challenges associated with poor breathability, inadequate wash stability, and difficult fabric integration. Within this broader context, our laboratory has previously developed heat-managing composite materials by drawing inspiration from the color-changing skin of the common squid. Herein, we describe the design, fabrication, and testing of breathable, washable, and fabric-integrated variants of our composite materials, which demonstrate state-of-the-art adaptive infrared properties and dynamic thermoregulatory functionalities. The combined findings directly advance the performance and applications scope of our bioinspired thermoregulatory composites and ultimately may guide the incorporation of desirable multifunctionality into other wearable technologies.

Increasing the efficiency of logistics for the area of storage and picking of special materials

The article deals with increasing the efficiency of logistics flows for the area of storage and picking. The aim of the processed study was to focus on the analysis of logistics activities and processes, the state of supply and inventory management. An assessment of the effectiveness of the introduced information system at the selected warehouse was carried out, which led to changes in a positive direction in the very process of storage and management of special products. The study presents the design of variants, the selection of the optimal one using selected decision-making methods and the introduction of a new warehouse system, which leads to the efficiency of the entire storage process in the NPI (New Product Introduction) warehouse. The output of the study is also the implementation of the selected variant into industrial practice, which is declared by the elaborated project of the introduction of the selected variant. The article is a contribution related to the process of implementing a warehouse and picking system for specialized material items.

Impact of the Location and Energy Carriers Used on Greenhouse Gas Emissions from a Building

The growth in population increases greenhouse gas (GHG) emissions into the environment. High GHG emissions are attributed to meat production, due to its high energy demand. The largest carbon footprint in the production of poultry meat is generated by combustion. This paper deals with the problem of greenhouse gas emissions (total dust, CO, CO2, NOx, SOx and benzo(a)pyrene) resulting from the generation of energy for heating broiler houses located in different locations in Europe. The study includes continuous measurements of selected microclimate parameters: temperature and relative humidity inside and outside the building, floor temperature, wind speed and direction, and solar radiation intensity. Validation and calibration of the model, emission calculations, and analysis of the obtained results were conducted. Eighteen design variants were assumed, differentiated by the heating fuel used (hard coal, fuel oil, gaseous fuels), material and construction solutions for the floor and the location of the facility. The analysis showed that CO2 emissions for a facility located in northern Europe are 123,153 kg higher compared to the same building located in southern Europe. In addition, increasing the floor’s thermal resistance by 3.69 m2·K·W−1 reduced harmful gas emissions by an average of 5.7% for each of the locations analysed.

Comparative study of stability and activity of wild-type and mutant human carbonic anhydrase II enzymes using molecular dynamics and docking simulations

The human carbonic anhydrase II (HCA II) enzyme is a cytosolic protein that catalyzes the reversible hydration of carbon dioxide (CO2). Considering the critical role of the HCA II and the effects of some mutations on the activity and stability of the enzyme in humans, several computational methods are used to study the structure and dynamics of the wild-type and the mutant enzymes with three ligands, CO2, 4-nitrophenyl acetate and acetazolamide. Our results of MD simulation of a wild-type enzyme with 4-nitrophenyl acetate show that it created essential effects on the fluctuation of this enzyme and made it more unstable and less compact than the same enzyme without ligand. In the MD of the mutant enzyme with 4-nitrophenyl acetate ligand, no significant difference is observed between with and without ligand. The affinity of the wild-type enzyme to the 4-nitrophenyl acetate is notably higher than the mutant enzyme with the same ligand. Furthermore, results showed that wild-type and mutant enzymes with CO2 are more favorable in stability and flexibility than the same enzymes without ligand. The MD results of wild-type with acetazolamide indicate instability compare without ligand, but in MD of mutant enzyme with acetazolamide show that it more stable and compact than the same enzyme without ligand. Finally, Comparing protein trajectories to assess the impact of ligands on the stability and activity of HCA II enzymes can have medical applications and can in the engineering and design of new variants of carbonic anhydrase enzyme.

An Investigation into Mechanical Properties of 3D Printed Thermoplastic-Thermoset Mixed-Matrix Composites: Synergistic Effects of Thermoplastic Skeletal Lattice Geometries and Thermoset Properties.

This study aims to develop thermoplastic (TP) and thermoset (TS) based mixed matrix composite using design dependent physical compatibility. Using thermoplastic-based (PLA) skeletal lattices with diverse patterns (gyroid and grid) and different infill densities (10% and 20%) followed by infiltration of two different thermoset resin systems (epoxy and polyurethane-based) using a customized FDM 3D printer equipped with a resin dispensing unit, the optimised design and TP-TS material combination was established for best mechanical performance. Under uniaxial tensile stress, the failure modes of TP gyroid structures with polyurethane-based composites included 'fiber pull-out', interfacial debonding and fiber breakage, while epoxy based mixed matrix composites with all design variants demonstrated brittle failure. Higher elongation (higher area under curve) was observed in 20% infilled gyroid patterned composite with polyurethane matrix indicating the capability of operation in mechanical shock absorption application. Electron microscopy-based fractography analysis revealed that thermoset matrix properties governed the fracture modes for the thermoplastic phase. This work focused on the strategic optimisation of both toughness and stiffness of mixed matrix composite components for rapid fabrication of construction materials.

Experimental assessment of strength characteristics of anthropogenic soils in a given mining area for justification of tractor propulsion type

BACKGROUND: In mining, there is a need to develop tractors as special robotic vehicles of the robotic mining facility that can efficiently move and work on soils with low bearing capacity, in waterlogged areas and in the underwater position. A preliminary evaluation of the strength characteristics of such a heterogeneous surface of the exploitation area helps to choose an effective concept and technical characteristics of the propulsor of the tractor. AIM: Formation of the database of the physical condition and mechanical properties of the environment in which the tractor will move and operate. METHODS: In order to achieve the aim, preliminary experiments were conducted on the terrain. Typical kinds of soil sites and watered areas, including those of anthropogenic origin, of a given mining area were identified. Full-scale instrumental tests were conducted to determine: granulometric composition of soils; physical and mechanical parameters of these soils at the selected sites using the developed original types of a penetrometer and a shear rig. RESULTS: The database of numerical values of measured strength characteristics of one of the soil types (as an example) as a possible supporting surface for vehicle motion in the area of mining facility operation is presented in a graphical form. The basis of this database is the graphs according to the results of experiments on free settlement and shear with the help of dies of two types of configuration (the round die and the original caterpillar track respectively); the granulometric composition of the selected soils has been evaluated. CONCLUSION: The methodology of preliminary assessment of the soil condition by two indicators of soil strength (the rut depth z depending on the average pressure under the die) and shear (average tangential stresses τ in the contact patch on the motion of the die relative to the soil, depending on the ratio of the normal force and the traction force in the contact plane) has been developed. The 3D model of the coastal and bottom area of the technogenic mining zone has been developed. Design variants of highly efficient types of tractor propulsors are selected on the basis of prediction of maximum allowable stresses in the contact patch with the ground for the bearing surface areas of the considered area of operation.