Construction Parameters Research Articles

Rapid prediction of airborne gaseous pollutant transport in aircraft cabins based on proper orthogonal decomposition and the Markov chain method

Rapid prediction of airborne gaseous pollutant transport is important for designing a safe indoor environment. Current models generally solve the airflow fields by CFD first and then predict the transport of a pollutant in fixed airflow patterns. Every time the air-supply parameters are adjusted, the airflow field must be re-solved by CFD, which is time-consuming. This study proposed a model to improve the prediction efficiency. The model first applies proper orthogonal decomposition to the sampled airflow fields, to construct a database related to all the airflow fields in the sample ranges, and then uses the Markov chain method to obtain the airflow field with the desired air-supply parameters for construction of a transport probability matrix. Finally, the airborne gaseous pollutant transport can be predicted quickly in the fixed airflow pattern. The proposed model was applied to an aircraft cabin model, first with a single gaseous pollutant source and then with two sources, for validation of the proposed model. The results show that the proposed model can predict both the airflow field and the transport of a gaseous pollutant with outcomes similar to those obtained by the conventional CFD method, but with a much shorter computing time. When the database has been prepared in advance, the use of the model reduces the computing time by more than 90%. Further improvement of the proposed model in terms of accuracy and extension of the model to prediction of pollutant transport within unsteady airflow fields will be the main objectives of future work.

Dietary Intake Contributed the Most to Chlorinated Paraffin Body Burden in a Norwegian Cohort.

Determining the major human exposure pathways is a prerequisite for the development of effective management strategies for environmental pollutants such as chlorinated paraffins (CPs). As a first step, the internal and external exposure to CPs were quantified for a well-defined human cohort. CPs in participants' plasma and diet samples were analyzed in the present study, and previous results on paired air, dust, and hand wipe samples were used for the total exposure assessment. Both one compartment pharmacokinetic modeling and forensic fingerprinting indicate that dietary intake contributed the most to body burden of CPs in this cohort, contributing a median of 60-88% of the total daily intakes. The contribution from dust ingestion and dermal exposure was greater for the intake of long-chain CPs (LCCPs) than short-chain CPs (SCCPs), while the contribution from inhalation was greater for the intake of SCCPs than medium-chain CPs (MCCPs) and LCCPs. Significantly higher concentrations of SCCPs and MCCPs were observed in diets containing butter and eggs, respectively (p < 0.05). Additionally, other exposure sources were correlated to plasma levels of CPs, including residence construction parameters such as the construction year (p < 0.05). This human exposure to CPs is not a local case. From a global perspective, there are major knowledge gaps in biomonitoring and exposure data for CPs from regions other than China and European countries.

Trends of digital transformation of construction organization processes in the conditions of critical influences

The article analyzes theoretical approaches to the formation of the process of digitalization of the economy and digital transformation of construction, interaction of project participants. It was found that critical influences on construction can be called such influences that completely disrupt the construction process of the object, or affect the size of the construction parameters (terms, labor intensity and cost) in such a way that the further construction process is either significantly complicated or impossible at all. Critical impacts can include any changes in the external and internal environment of the construction project, including floods, natural disasters, etc.The review of literary sources made it possible to highlight the main problems, the solution of which is necessary for the proper theoretical justification of the action of critical influences on the process of construction organization and its digital transformation,Theoretical substantiation of the role of critical influences on the transformation of the construction process made it possible to identify the following consequences of the influence of military actions on the construction industry during the war in Ukraine. Such factors were the change in the company’s supply chains and the lack of many material, technical and human resources in construction, the destruction of the existing information structure that needs to be constantly restored, the direction of investment priorities towards the defense of the country, a decrease in investments in digitalization, a significant migration of the population, the growth of cyber threats, the need for cyber protection system, etc.The identification of critical influences on the process of construction organization and on digital transformation will allow enterprises and organizations of the construction complex, various participants in investment and construction projects not only to classify them according to the degree of influence on a separate enterprise, but also to develop a set of preventive or smoothing measures regarding the functioning of participants in the digital environment of the project.

Prediction of Primary Deformation Modulus Based on Bearing Capacity: A Case on Forest Road with a Light Falling Weight Deflectometer Zorn ZFG 3000 GPS

Bearing capacity and compaction are among the most important and frequently used geotechnical parameters in road construction. The aim of this study was to determine the possibility of predicting the value of the primary deformation modulus E1 (obtained from measurements using a static plate load test—PLT) based on measurements with a Zorn light falling weight deflectometer (LFWD), type ZFG 3000 GPS, with a drop weight of 10 kg. A regression analysis was performed on 245 bearing capacity measurements that were taken on 46 forest road sections with various road surfaces. Different regression models were tested, from linear to logarithmic, polynomial, exponential and power models, but excluding polynomials of fourth and higher degree. The results showed that the prediction of E1 values (PLT) from the dynamic deformation modulus values Evd (LFWD) was possible. However, the reported unsatisfactory strength of the relationship between the two parameters was associated with a high risk of error (r = 0.64, R2 = 0.41, Se = 49.78). Neither the use of more complex non-linear regression models, nor the use of multiple regression by introducing an additional estimator in the form of the s/v ratio, significantly improved estimation results. The quality of the prediction of the E1 value was not constant. It varied, depending on the type of forest road, the use of geosynthetic reinforcement and the type of road subgrade. During the study, it was also found that the quality of the prediction of the E1 value could be improved by limiting the range of Evd values tested from above. It is advisable to continue this type of research, as the obtained results could form the basis for future development of national standards for the use of LFWDs to control the bearing capacity and compaction of forest road pavements.

Probabilistic Analysis of Slope against Uncertain Soil Parameters

The purpose of this article was to investigate the influence of uncertain soil parameters on slope stability problems using the probability method. The most important soil instability is probably the inherent spatial variability of soil properties and its influence on slope safety factors. The probability method is recognized for its validity both in practice and academic research. This method of geotechnical risk management involves uncertain parameters. In this study, randomly selected uncertain parameters were combined with traditional analysis using Bishop’s simple methodology and Monte Carlo simulation. The minimum safety factor and critical slip surface of the slope stability were analyzed by Bishop’s simple method. The influence of uncertain soil parameters was analyzed by the back analysis method with Monte Carlo simulation. The calculation was controlled by a critical slip surface, and the safety factor was equal to 1. The results of the analysis show the minimum safety factor and the significant slippery surface of slope stability with the original soil strength parameters. The new soil strength parameters were recommended by Monte Carlo simulation that was used for improving the soil strength parameters in construction. In addition, probability analysis can identify an insufficient understanding of groundwater level distribution and that the assumption of a uniform distribution increases the probability of failure. Governments can use the results of water level analysis in flood warnings and flood management projects to reduce risks to life and property.

One-step co-sintering of hierarchical mullite whisker/fiber membranes with gradient pore structures for effective filtration of dust-laden gas

Porous ceramic fiber membranes with high gas permeance have shown great potential for the treatment of dust-laden gas. However, a major challenge is posed by the micro or nano-sized solid particles which can easily block the pore channels of the fiber membranes due to the larger surface pore size. Therefore, in this work, a novel method was proposed for the in-situ growth of mullite whiskers around the surface of the mullite fibers. This method aimed to decorate the pore channels of the fiber membranes by using a layer-by-layer construction strategy. For this purpose, a dry-pressing technique was employed to prepare a “green” mullite fiber support. It was followed by the preparation of another “green” fiber layer with the addition of catalysts on this support. After the co-sintering process, hierarchical mullite whiskers with gradient pore structures were produced. The in-situ growth of mullite whiskers around the fibers decorated the pore structure. As a result, it helped in effectively capturing the solid particles in the dust-laden gas. Additionally, the co-sintering process significantly reduced the sintering consumption and fabrication period. Moreover, a detailed investigation was carried out on the construction parameters including the sintering system atmospheres, Si–Al sol addition content, AlF3 concentration, mechanism of whisker growth and stability. The findings showed that hierarchical mullite whisker/fiber membranes obtained from the proposed method had a mean pore size of 2.7 μm and gas permeance of ∼106 m3 m−2 h−1·kPa−1. The Darcy's permeability coefficient of the membranes was also higher than the membranes prepared from existing methods. Moreover, the optimized membrane showed 99.9% rejection of the solid particles in the dust-laden gas, including micron-size (2.5 μm) and nano-size (300 nm) solid particles. This work provides a novel method for the fabrication of hierarchical mullite whiskers with gradient pore structures having the capability to filter industrial dust-laden gas.

High speed stereoscopic PIV investigation of the statistical characteristics of the axially restricted turbulent swirl flow behind the axial fan in pipe

Investigation of the turbulent swirl flow in the piping system is one of the most complex investigations in the field of energetics and turbulence. Axial fans in a pipe, without guide vanes, are widely used in practice and the problem of their duty point and energy efficiency is still extensively discussed. Analysis of the interaction between axial fans energy and construction parameters is one of the main topics in defining the fans energy efficiency potential. On one side, there is a three-dimensional velocity field in the wall-bounded flow with regions of great turbulence intensity. On the other side, there is a complex blade geometry, which generates the turbulent swirl flow. This paper presents research on the turbulent swirl flow, Rankine type, in an axially restricted system, using high-speed stereo particle image velocimetry (HSS PIV). Axial fan impeller, with outer diameter 0.399 m and nine twisted blades is the flow generator. The Reynolds number Re = 176,529 is achieved in the pipe. Reynolds stresses, statistical moments of higher order, and invariant maps are calculated based on the three component velocity fields. Here, intensive changes of all statistical parameters occur in radial and axial direction. In the flow region, four flow regions can be identified. Interaction of all these four flow regions produces extremely complex turbulent swirl flow, which is generated behind the axial fans. Determined invariant maps reveal turbulence structure. It is shown that the state of turbulence on the pipe axis is three-component isotropic, which is contrary to the case of axially unrestricted turbulent swirl flows. In the rest of the space, in the region up to r/ R = 0.52, the states of turbulence occur in the area in between the boundaries which designate axis-symmetric turbulence (contraction) and axis-symmetric turbulence (expansion), in the vicinity of the state of three-component isotropic turbulence.

Hydraulic fracture to enhance coalbed methane recovery by using coated ceramsite

AbstractIn recent decades, coated ceramsite has become popular due to its low density, high compressive strength, and high flow conductivity, and it has been applied in many areas in construction field and chemical industry. In the area of hydraulic fracture, limited relevant literature can be found, especially on unconventional reservoirs with soft coals. In this paper, numerical simulation is performed to obtain migration regularity and granularity proportion using coated ceramsite, and it indicates that the biggest proppant concentration and strongest flow conductivity can be achieved under the granularity proportion of 1:6:2 with respective coated ceramsites of 40/60, 16/40, and 12/20 mesh. Then, a series of construction parameters are calculated and optimized to receive a best fracture performance by using mathematical methods, including total proppant volume, each proppant volume, fluid injection rate, fluid injection volume, and proppant concentration, etc. Results from micro seismic monitoring indicate that the actual fracture performance matches well with the simulated performance by using coated ceramsite and has an obviously longer fracture length and a bigger proppant concentration compared with performances by using quartz sand. Meanwhile, comparisons for gas productions fractured by coated ceramsite and quartz sand reveal that coated ceramsite can achieve a better drainage performance. All of the above can be a guide for hydraulic fracture and useful for enhancing coalbed methane recovery. © 2022 Society of Chemical Industry and John Wiley &amp; Sons, Ltd.

Analysis of the axial and transversal stiffness of an air spring suspension of a railway vehicle: mathematical modelling and experiments

ABSTRACT The secondary suspension of railway vehicles is fundamental for their dynamic behaviour. This paper outlines a model-based procedure for predicting and evaluating the influence of different parameters in the static stiffness and vibration transmission of an air spring employed in the secondary suspension system of a railway vehicle. For that aim, a detailed and experimentally validated finite element model of the air spring is defined. It includes the behaviour of the reinforced elastomer, the inner pressure-deformation coupling and the thermodynamic interactions taking place inside the bellow. A Computer Aided Design of Experiments is employed to evaluate the influence of seven construction parameters of the bellow. Experimental tests and simulation results show that the air spring has natural frequencies below 100 Hz, in the frequency range where structure-borne vibration transmission occurs. The cord angle modifies the axial-transversal stiffness relation and a larger separation between adjacent layers and fibres delay the vibration transmissibility.

Mechanism Study of the Effect of Selective Laser Melting Energy Density on the Microstructure and Properties of Formed Renewable Porous Bone Scaffolds

To investigate the effect of selective laser melting (SLM) energy densities on the performance of porous 316L stainless steel bone scaffolds, the porous bone scaffolds with a face-centered cubic (FCC) structure were prepared using SLM technology, and a comprehensive study combining finite element analysis (FEA) and experiments was conducted on the SLM-formed 316L porous bone scaffolds. The mechanism of how various energy densities affect bone scaffolds were identified, and the effects of different energy densities on the primary dendrite spacing, grain orientation, residual stress, and transient melt pool variation in the scaffolds were discussed and summarized. It was found that the change in the energy densities had a more serious effect on the primary dendrite spacing, with the primary dendrite spacing increasing from 320 to 501 nm when the energy densities were increased from 41.7 to 111.1 J/mm3. In addition, analysis of the residual stress in the formed scaffolds showed that when an energy density of 41.7 J/mm3 was chosen for construction, the internal residual stress in the scaffolds reached a minimum value of 195.78 MPa, a reduction of approximately 36.6% compared to that of 111.1 J/mm3 for the porous scaffold. For the other properties of the scaffolds, the choice of low energy densities for the construction of FCC-structured porous bone scaffolds allowed for a maximum 10% reduction in the controlled deformation and a maximum 17% increase in the compressive properties. At the same time, it was found that the analysis results of the SLM-forming process by the FEA method were consistent with the experimental results. The main innovation of this paper is the proposal of the best construction parameters for porous bone scaffolds with an FCC structure formed by SLM and verification of the rationality of the best parameters through macro and micro experimental analysis, which guides the construction of porous bone scaffolds with an FCC structure formed by additive manufacturing. In addition, this study used finite element simulation to analyze the SLM process. This provides early prediction, optimization, and improvement for SLM-forming FCC porous bone scaffolds. The most important thing is that FEA can be used to more rapidly and economically analyze SLM. In the future, FEA can be used to provide a reference for porous bone scaffolds with different structures, different construction energy densities, different materials, and additive manufacturing in other industries.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of &gt;130 000 DFT calculations to 10000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Structural modelling of 100% cotton single jersey fabrics for optimum UV protection

PurposeLightweight, open construction cotton knitted fabrics generally do not impart good protection from solar ultraviolet radiation (UVR). As lightweight 100% cotton single jersey is highly cherished for summerwear, it is sine qua non to understand the structural parameters that effectively strike a good balance between UV protection and thermophysiological comfort of the wearer. Relatively heavy fabrics protect from UVR, but comfort is compromised because of waning porosity, increase in thickness and thermal insulation. The purpose of this paper is to engineer knits that will bestow maximum UV protection while preserving the thermophysiological comfort of the wearer.Design/methodology/approachIn total, 27 cotton single jersey fabrics with different areal densities and yarn counts were selected. Ultraviolet protection factor (UPF) was calculated based on the work of Imrith (2022). To précis, the authors constructed a UV box to measure the UPF of fabrics, denoted as UPFB. UPFB data were correlated with AATCC 183-2004 and yielded high correlation, R2 0.977. It was concluded that UPF 50 corresponds to UPFB 94.3. Thermal comfort properties were measured on the Alambeta and water-vapour resistance on the Permetest. Linear programming (LP) was used to optimize UPFB and comfort. Linear optimization focused on maximizing UPFB while keeping the thermophysiological comfort and areal density as constraints.FindingsThe resulting linear geometrical and sensitivity analyses generated multiple technically feasible solutions of fabrics thickness and porosity that gave valid UPFB, thermal absorptivity and water-vapour and thermal resistance. Subsequently, an interactive optimization software was developed to predict the stitch length, tightness factor and yarn count for optimum UPFB from a given areal density. The predicted values were then used to knit seven 100% cotton single jersey fabrics and were tested for UV protection. All seven fabrics gave UPFB above the threshold, that is, higher than 94.3. The mathematical model demonstrated good correlations with the optimized parameters and experimental values.Originality/valueThe optimization software predicted the optimum UPFB reasonably well, starting from the fabric structural and constructional parameters. In addition, the models were developed as interactive user interfaces, which can be used by knitted fabric developers to engineer cotton knits for maximizing UV protection without compromising thermophysiological comfort. It has been demonstrated that LP is an efficient tool for the optimization and prediction of targeted knitted fabrics parameters.

In-plane seismic behavior of lightweight steel drywall façades through quasi-static reversed cyclic tests

A lightweight steel (LWS) drywall façade is one of the most widely used architectural non-structural components in a building. This paper presents the results of in-plane quasi-static reserved cyclic tests carried out on 14 different full-scale façades made with LWS framing. The main goal of the study is to investigate the effect of various construction details on the seismic response of the selected facades. The investigated parameters include single or double frame walls, type of sheathing panels, presence of finishing, variation in surrounding constructional elements, absence of track members, type of connection to the surrounding constructional elements, and presence of protrusion. The effect of the construction parameters on the lateral response of the façades was examined in terms of strength, stiffness, force–displacement hysteretic response, and damage mechanisms. Therefore, the damage phenomena observed during the tests are reported, associating them with the three damage limit states based on the level of damage. For the definition of seismic vulnerability, the fragility curves for different façade typologies are also presented. Finally, based on the fragility data, the evaluation of seismic performance according to IDR limits for non-structural components given by Eurocode 8 is also performed.

Coupling model of stress-damage and its application to static blasting technology

To improve the gas drainage effect of low-permeability coal seams, the influence of the hole arrangement on the static blasting effect was studied through single-hole, double-hole, and guiding-hole blasting tests. A stress-damage coupling model was established to reveal the evolution of the stress field and the distribution of the damage zone under different construction parameters, and the evolution law of the damage zone under a multi-hole arrangement was investigated. The following can be inferred from the research results. (1) The crack initiation of double holes depends on the stress superposition between blasting holes, whereas that of guiding holes depends on the free surface inside the coal body. The increase in borehole diameter and spacing reduction between boreholes could improve the static superposition breaking effect. (2) The relationship between the guiding hole, borehole diameter, and borehole spacing was revealed from the two aspects of the stress field and damage zone. The purpose is to strengthen the blasting effect. The drilling diameter and spacing are measured, and the guiding hole strengthens the blasting effect. At the measurement level, it should be analyzed from the two dimensions of time and stress. The time dimension accelerates the migration of the stress turning point, whereas the stress dimension realizes stress superposition and finally strengthens the static cracking effect. (3) The damage zone evolution of static blasting technology is influenced by expansion pressure, construction parameters, and elastic modulus. The increase in the expansion pressure caused the damage zone of the coal body and a decrease in the elastic modulus. Under the combined action of the expansion pressure and elastic modulus, the damage zone expanded and penetrated. The guiding borehole would not only have a guiding function but could also enhance the breaking effect. (4) In the simulation test scheme, the reasonable ratio of borehole spacing to borehole diameter is approximately 13 to 14, and the reasonable construction parameters are 113 mm of borehole diameter, 1.4 m of borehole spacing, and the layout of multi-hole-guiding hole. Static blasting technology can increase the distribution of the damaged areas of coal seams, realize pressure relief and permeability enhancement of coal seams, and improve the safe construction of coal mining.

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.

Methodology of justification and calculation of rational and constructive parameters of a tube belt conveyor

The article considers the methodology of justification and calculation of rational and constructive parameters of a tube belt conveyor (TBC), which allows to transport bulk cargo safely.At the same time, there was noted the need for a harmless impact on the environment, especially when transporting routes with vertical and horizontal bends over long distances.The considered TBC design, unlike the existing ones, is formed with a closed belt tray due to support devices placed along the perimeter of the bulk cargo transportation line.It is revealed that the main advantages of conveyor transport are a high level of labor productivity achieved by automating the operation of equipment and low production costs. And the problems inherent in them are the need for crushing the transported cargo, precise alignment of transition sections, coordination of drives and synchronization of movements, easily adjustable during operation, subject to certain initial design conditions.

Analysis of the main design and operating parameters of the device for the fermentation of bird droppings

The study on the utilization of poultry droppings put forward the need for the constructive and technological improvement of the biofermentation device. A drum-type bioreactor better meets the requirements for the technological process of eco-friendly biologically active fertilizer production from livestock and poultry wastes. However, the great size of the heat transfer surface of the bioreactor drum and its significant ejection momentum during spinning require quite a lot of energy. To decrease this consumption, the main constructive parameters should be optimized. The main reason is the sharp increase in prices for mineral fertilizers, the weak economic condition of most farms, the lack of advanced processing technologies and the use of organic fertilizers.&#x0D; Our aim in these studies was to analyze the types of design and operating parameters of the device for the fermentation of bird droppings. To this end, we conducted a study on the disposal of bird droppings, and also put forward the need for constructive and technological improvement of the biofermentation device. One of such ways to solve the problem was a drum-type bioreactor, which, according to our research indicators, better meets the requirements for the technological process of producing environmentally friendly biologically active fertilizers from animal husbandry and poultry waste, however, the size of this equipment of the heat transfer surface of the bioreactor drum and its significant emission pulse during rotation require a rather large waste of energy. To reduce this consumption, it is necessary to optimize the basic design parameters.&#x0D; Devices that work continuously were recognized as the most promising. They fully meet the technological and operational requirements

Mechanical rotor unbalance monitoring based on system identification and signal processing approaches

Mechanical unbalance is an important source of vibrations that can cause malfunctions in rotodynamic machinery. In industrial applications, unbalance is a critical issue for mass production machines. Previous studies for detecting and monitoring unbalance are based on balancing machines, trial weights, and intrusive actuators, while other studies rely on signal processing techniques, finite element analysis and physical modeling. These methodologies have some critical drawbacks, especially when non-intrusive monitoring is required, such as having to trial weights or determine constructive parameters such as mass and stiffness. The proposed approach is based on detecting and monitoring the unbalance condition in rotatory machines using data extracted from vibration sensors and a rotation sensor fitted to the system supports. The methodology comprises two main steps: identifying the appropriate speed range for unbalance monitoring and the modal parameters of the rotor, and determining and continuously monitoring the unbalance condition. Signal processing and system identification techniques are used to estimate unbalance in the rotatory machine. Experimental results for two rotodynamic systems demonstrate satisfactory performance in identifying and monitoring different unbalance conditions.

Deep Learning Method on Deformation Prediction for Large-Section Tunnels

With the continuous development of engineering construction in China, more and more large-section highway tunnels have emerged. Different geological engineering environments determine the diversity of construction plans. The determination of construction plans and the prediction of tunnel deformations have always been the key points of engineering construction. In this paper, we use numerical simulations to determine specific construction parameters in the context of actual highway tunnel projects, and then use deep learning methods to predict deformation during tunnel construction, thus providing guidance for construction. We have found that: (i) Different excavation sequences and excavation depths have different effects on the surrounding rock deformation around the tunnel. The optimal excavation sequence through numerical simulation in this study is symmetrical excavation, and the excavation depth is 2 m. (ii) Numerical simulation based on Long Short-Term Memory (LSTM) algorithm is used to predict the tunnel deformation. It is found that the prediction results of the LSTM algorithm are more consistent with the actual monitoring data. (iii) Multi-step prediction is more important for engineering guidance, and three-step prediction can be considered during the process of engineering construction. Therefore, the machine learning algorithm provides a new method for engineering prediction.

Evaluation of Protective Clothing against Chemical and Fire Hazards

Workplace accidents are very unpredictable. Protection against these risks and hazards is of utmost importance in every profession. Clothing has always been considered one of the integral parts of personal protective equipment. The present study aims at manufacturing and evaluating protective clothing materials used by chemical workers. It was experimental. Two important resistance characteristics; chemical and fire were assessed against international performance standards. The results highlighted the fact that the right selection of construction parameters was able to make a safe fabric against such hazards. The resultant fabric was evaluated at various washing intervals and was found to be resistant to four selected chemicals through penetration and repellency index. It was also able to resist fire by passing the standard after flame and char length tests. Very little research work has been done in Pakistan regarding the manufacturing and physical assessment of clothing materials used by chemical workers. This study aimed to approach the target area where the protection and safety of the worker should be a priority.