A Multiscale Simulation Method and Its Application to Determine the Mechanical Behavior of Heterogeneous Geomaterials

To study the micro/mesomechanical behaviors of heterogeneous geomaterials, a multiscale simulation method that combines molecular simulation at the microscale, a mesoscale analysis of polished slices, and finite element numerical simulation is proposed. By processing the mesostructure images obtained from analyzing the polished slices of heterogeneous geomaterials and mapping them onto finite element meshes, a numerical model that more accurately reflects the mesostructures of heterogeneous geomaterials was established by combining the results with the microscale mechanical properties of geomaterials obtained from the molecular simulation. This model was then used to analyze the mechanical behaviors of heterogeneous materials. Because kernstone is a typical heterogeneous material that comprises many types of mineral crystals, it was used for the micro/mesoscale mechanical behavior analysis in this paper using the proposed method. The results suggest that the proposed method can be used to accurately and effectively study the mechanical behaviors of heterogeneous geomaterials at the micro/mesoscales

Progress in biological and medical research in the deep underground: an update

As the growing population of individuals residing or working in deep underground spaces for prolonged periods, it has become imperative to understand the influence of factors in the deep underground environment (DUGE) on living systems. Heping Xie has conceptualized the concept of deep underground medicine to identify factors in the DUGE that can have either detrimental or beneficial effects on human health. Over the past few years, an increasing number of studies have explored the molecular mechanisms that underlie the biological impacts of factors in the DUGE on model organisms and humans. Here, we present a summary of the present landscape of biological and medical research conducted in deep underground laboratories and propose promising avenues for future investigations in this field. Most research demonstrates that low background radiation can trigger a stress response and affect the growth, organelles, oxidative stress, defense capacity, and metabolism of cells. Studies show that residing and/or working in the DUGE has detrimental effects on human health. Employees working in deep mines suffer from intense discomfort caused by high temperature and humidity, which increase with depth, and experience fatigue and sleep disturbance. The negative impacts of the DUGE on human health may be induced by changes in the metabolism of specific amino acids; however, the cellular pathways remain to be elucidated. Biological and medical research must continue in deep underground laboratories and mines to guarantee the safe probing of uncharted depths as humans utilize the deep underground space

Reflections and explorations on deep earth science and deep earth engineering technology

Deep earth science in the 21st century has entered a new stage of development. The laws of deep earth science have not yet been explored. Deep engineering activities generally have a certain degree of blindness, inefficiency and uncertainty, and the endogenous dynamics of the Earth’s deep part, structural evolutionary laws, and disaster-causing mechanisms need to be further cognised. Therefore, this paper firstly defines deep earth science from the perspective of geoscience: the deep and ultra-deep layers of the earth are the research objects from the shallow earth to the deep, aiming at exploring the scientific mysteries of the earth’s different layers and different depths of the earth (deep and ultra-deep); clarifies the difference and connection between the deep earth science and the earth science: that is to say, the deep earth science is an extension of the known knowledge system of the earth science, and it is the national strategic science and technology direction to expand the scientific horizons, and to deepen the earth’s cognition. It is a national strategic scientific and technological direction to expand scientific vision and deepen earth knowledge, which is included in earth science; it defines the essence of deep and deep earth engineering science: that is, for the difficulties that the existing scientific laws and technologies of shallow engineering cannot be applied to deep engineering, it is necessary to explore the relevant scientific laws of deep engineering, break through the key basic scientific problems of deep engineering, and meet the demand for geo-disaster prevention and control of human beings in the activities of deep engineering, and then guide the safe, efficient, and green development of deep resources and effective utilization of the space of deep engineering; at the same time, it further clarifies the difference and connection between deep earth science and earth science. This article proposes the definition of deep earth engineering technology, which refers to the engineering implementation technology and equipment required by humans to utilize and develop the Earth, as well as the necessary theoretical and technical means to explore the laws of deep earth science and develop deep earth engineering. Finally, to promote the development of deep earth science, the research content and strategic planning of deep earth science, and the connotation of deep earth engineering technology, have been further clarified (geomechanics and disaster mechanism of deep-earth engineering, intelligent construction and efficient mining, intelligent construction of deep-earth tunnels and giant cavern groups, intelligent disaster prevention and control as well as healthy operation and maintenance of deep-earth engineering)

Neural network-based optimal iterative controller for nonlinear processes

A new optimal iterative neural network-based control (OINNC) strategy with simple computation and fast convergence is proposed for the control of processes with nonlinear dynamics. The process dynamics is captured by a forward neural network, and the control is determined by a simple iterative optimization during each sampling interval bated on a linearized neural network model. In addition, a feedback control is incorporated into the system to compensate for any model mismatches and to reject disturbances. With the proposed system, the tracking error is shown to be confined to the origin. An application of the proposed OINNC scheme to a nonlinear process results in superior performance when compared with a well-tuned conventional PID controller

Effect of Continuous Loading Coupled with Wet–Dry Cycles on Strength Deterioration of Concrete

In practical engineering, concrete is often under continuous stress conditions and there are limitations in considering the effect of wet–dry cycles alone on the strength deterioration of concrete. In order to study the deterioration of concrete strength under the coupling of load and wet-dry cycles, concrete specimens were loaded with 0%, 10%, 20%, and 35% stress levels and coupled to undergo one, three, and seven wet–dry cycles. The strength deterioration of the concrete was obtained by uniaxial compression and the regression equation was established. The strength deterioration mechanism of the concrete under the coupled conditions was analyzed and revealed through an AE acoustic emission technique and nuclear magnetic resonance technique. The results of the study show that, with the same number of wet–dry cycles, there are two thresholds of a and b for the uniaxial compressive strength of concrete with the stress level, and with the progression of wet–dry cycles, the length of the interval from a to b gradually shortens until it reaches 0. The cumulative AE energy of concrete decreases with the progression of wet–dry cycles; using the initiating crack stress as the threshold, the calm phase of concrete acoustic emission, the fluctuating phase, and the NMR T2 spectral peak area show different patterns of variation with the increase in the number of wet–dry cycles

PID-based sliding mode controller for nonlinear processes

Sliding mode control (SMC) has excellent robustness to model uncertainties and disturbances. This would make SMC an ideal scheme for process control applications where model uncertainties and disturbances are common. The existing SMC, however, has the major drawback of control chattering; i.e., the controller output is a discontinuous high-frequency switching signal. This makes SMC not suitable for most chemical processes where the manipulated variables are continuous and where high-frequency changes are not permitted. To eliminate chattering, a new proportional-integral-derivative (PID)-based sliding mode control (PIDSMC) suitable for the chemical process is proposed here. The proposed control system consists of three components: a compensation of process nonlinearity, a linear feedback of state tracking errors, and a PID control of the sliding surface function. The chattering is eliminated via the replacement of the discontinuous switching in the SMC by a continuous input determined by a PID scheme. An adaptive strategy is proposed to tune the PID parameters online to control the process states onto a sliding surface that characterizes the closed-loop performance. The proposed algorithm has been shown to be effective in controlling an inverted pendulum system and a typical pH neutralization process

Numerical Simulation of the Influence of Width of a Prefabricated Crack on the Dimensionless Stress Intensity Factor of Notched Semi-Circular Bend Specimens

To analyze the effect of the width of a prefabricated crack on the dimensionless stress intensity factor of notched semi-circular bend (NSCB) specimens, ABAQUS software was employed to perform numerical calibration of the crack tip stress intensity factor for the width of prefabricated cracks in the range of 0.0∼2.0 mm. The relative errors of the dimensionless stress intensity factor for different widths of prefabricated cracks were analyzed. The results indicate that the dimensionless stress intensity factor shows an approximate linear increase as the width of the prefabricated crack increases. The longer is the length of the prefabricated crack, the “faster” is the increase in speed. The effect of the dimensionless support spacing on the increase in the speed of the dimensionless stress intensity factor due to the increase in crack width is minimal. When the prefabricated crack width is 2.0 mm, the maximum relative error of the dimensionless stress intensity factor is 4.325%. The new formula for the dimensionless stress intensity factor that eliminates the influence of the width of a prefabricated crack is given, which provides a theoretical basis for the more accurate fracture toughness value measured using an NSCB specimen

Identification and control of nonlinear processes in the presence of unmeasured load disturbances

Identification and control of a nonlinear process in the presence of unmeasured load disturbances is important, because most chemical processes are perturbed by load disturbances that are often not measured. In this paper, the absorption principle is first extended to develop an effective identification strategy for a feedforward neural network representation of the process input-output relation in the presence of an unmeasured load disturbance. This developed model can provide an accurate output prediction, irrespective-of the load disturbances, as long as the disturbances can be reasonably approximated by piecewise polynomials. Second, a predictive control scheme is developed on the basis of genetic algorithm optimization, using the above-identified model, for the nonlinear process under the influence of unmeasured loads. Finally, simulations are provided to illustrate the effectiveness of the proposed identification and control scheme

An analytical predictive control law for a class of nonlinear processes

Many processes in the chemical industry have modest nonlinearities; i.e., linear dynamics play a dominant role in governing the process output behavior in the operating range of interest, but the linearization errors may be significant. For these types of processes, linear-based control may yield a poor performance, while nonlinear-based control results in computation complexity. We propose to model this type of process with a composite model consisting of a linear model (LM) and a multilayered feedforward neural network (MFNN). The LM is used to capture the Linear dynamics, while the MFNN is employed to predict the LM's residual errors, i.e., the process nonlinearities. Effective off-line and on-line al,algorithms are proposed for the identification of the composite model. With this model structure, it is shown that a simple analytical predictive control law can be formulated to control a nonlinear process. Simulation examples are also given to illustrate the effectiveness of the model identification and the proposed predictive control

Effect of Continuous Loading Coupled with Wet–Dry Cycles on Strength Deterioration of Concrete

In practical engineering, concrete is often under continuous stress conditions and there are limitations in considering the effect of wet–dry cycles alone on the strength deterioration of concrete. In order to study the deterioration of concrete strength under the coupling of load and wet-dry cycles, concrete specimens were loaded with 0%, 10%, 20%, and 35% stress levels and coupled to undergo one, three, and seven wet–dry cycles. The strength deterioration of the concrete was obtained by uniaxial compression and the regression equation was established. The strength deterioration mechanism of the concrete under the coupled conditions was analyzed and revealed through an AE acoustic emission technique and nuclear magnetic resonance technique. The results of the study show that, with the same number of wet–dry cycles, there are two thresholds of a and b for the uniaxial compressive strength of concrete with the stress level, and with the progression of wet–dry cycles, the length of the interval from a to b gradually shortens until it reaches 0. The cumulative AE energy of concrete decreases with the progression of wet–dry cycles; using the initiating crack stress as the threshold, the calm phase of concrete acoustic emission, the fluctuating phase, and the NMR T2 spectral peak area show different patterns of variation with the increase in the number of wet–dry cycles