宏阳煤矿薄煤层沿空留巷实践应用

为了缓解矿井采掘接替紧张局面,宏阳煤矿采用沿空留巷技术,对12102运输顺槽采取顶板超前采面打设锚索梁、顶板超前预裂爆破,留巷段采用“钢梁+单体液压支柱”的方式进行巷道支护。该技术现场应用后,减少了巷道掘进工程量,减少了煤炭损失,增加了经济效益,降低了职工劳动强度,有利于采掘接替。     

The influence of the waveguide on the quality of measurements with ultrasonic Doppler velocimetry

The article is devoted to the study of the influence of geometric parameters of sound-conducting walls on the quality of measurement of liquid metal flow velocities by ultrasonic Doppler velocimetry. It was shown that the thickness and radius of a sound-conducting wall (waveguide) have a notable effect on the resulting velocity profiles. The flow in a round pipe, the length of which is much larger than its diameter, is considered as a reference flow. The positive effect of a stepwise waveguides with a diameter smaller than the diameter of the piezoelectric element of an ultrasonic transducer on the quality of velocity measurements was verified experimentally. It was found that the accuracy of the resulting velocity profiles largely depends on the length and the material of the waveguides, as well as the velocity of the incoming flow of liquid metal.     

The Interplay of Modulus,Strength, and Ductility in Adhesive Design Using Biomimetic Polymer Chemistry

High‐performance adhesives require mechanical properties tuned to demands of the surroundings. A mismatch in stiffness between substrate and adhesive leads to stress concentrations and fracture when the bonding is subjected to mechanical load. Balancing material strength versus ductility, as well as considering the relationship between adhesive modulus and substrate modulus, creates stronger joints. However, a detailed understanding of how these properties interplay is lacking. Here, a biomimetic terpolymer is altered systematically to identify regions of optimal bonding. Mechanical properties of these terpolymers are tailored by controlling the amount of a methyl methacrylate stiff monomer versus a similar monomer containing flexible poly(ethylene glycol) chains. Dopamine methacrylamide, the cross‐linking monomer, is a catechol moiety analogous to 3,4‐dihydroxyphenylalanine, a key component in the adhesive proteins of marine mussels. Bulk adhesion of this family of terpolymers is tested on metal and plastic substrates. Incorporating higher amounts of poly(ethylene glycol) into the terpolymer introduces flexibility and ductility. By taking a systematic approach to polymer design, the region in which material strength and ductility are balanced in relation to the substrate modulus is found, thereby yielding the most robust joints.     

Interleukin-1β Modulation of the Mechanobiology of Primary Human Pulmonary Fibroblasts: Potential Implications in Lung Repair

Pro-inflammatory cytokines like interleukin-1β (IL-1β) are upregulated during early responses to tissue damage and are expected to transiently compromise the mechanical microenvironment. Fibroblasts are key regulators of tissue mechanics in the lungs and other organs. However, the effects of IL-1β on fibroblast mechanics and functions remain unclear. Here we treated human pulmonary fibroblasts from control donors with IL-1β and used Atomic Force Microscopy to unveil that IL-1β significantly reduces the stiffness of fibroblasts concomitantly with a downregulation of filamentous actin (F-actin) and alpha-smooth muscle (α-SMA). Likewise, COL1A1 mRNA was reduced, whereas that of collagenases MMP1 and MMP2 were upregulated, favoring a reduction of type-I collagen. These mechanobiology changes were functionally associated with reduced proliferation and enhanced migration upon IL-1β stimulation, which could facilitate lung repair by drawing fibroblasts to sites of tissue damage. Our observations reveal that IL-1β may reduce local tissue rigidity by acting both intracellularly and extracellularly through the downregulation of fibroblast contractility and type I collagen deposition, respectively. These IL-1β-dependent mechanical effects may enhance lung repair further by locally increasing pulmonary tissue compliance to preserve normal lung distension and function. Moreover, our results support that IL-1β provides innate anti-fibrotic protection that may be relevant during the early stages of lung repair.     

The control of sea lice in Atlantic salmon by selective breeding

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production.     

Model repair — aligning process models to reality

Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Process models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior. Existing process mining techniques can only uncover these differences, but the actual repair of the model is left to the user and is not supported. In this paper we investigate the problem of repairing a process model w.r.t. a log such that the resulting model can replay the log (i.e., conforms to it) and is as similar as possible to the original model. To solve the problem, we use an existing conformance checker that aligns the runs of the given process model to the traces in the log. Based on this information, we decompose the log into several sublogs of non-fitting subtraces. For each sublog, either a loop is discovered that can replay the sublog or a subprocess is derived that is then added to the original model at the appropriate location. The approach is implemented in the process mining toolkit ProM and has been validated on logs and models from several Dutch municipalities.     

Alloying behavior and novel properties of CoCrFeNiMn high-entropy alloy fabricated by mechanical alloying and spark plasma sintering

An equiatomic CoCrFeNiMn high-entropy alloy was synthesized by mechanical alloying (MA) and spark plasma sintering (SPS). During MA, a solid solution with refined microstructure of 10 nm which consists of a FCC phase and a BCC phase was formed. After SPS consolidation, only one FCC phase can be detected in the HEA bulks. The as-sintered bulks exhibit high compressive strength of 1987 MPa. An interesting magnetic transition associated with the structure coarsening and phase transformation was observed during SPS process.     

Quantitative risk assessment using a Japanese hydrogen refueling station model

Although hydrogen refueling stations (HRSs) are becoming widespread across Japan and are essential for the operation of fuel cell vehicles, they present potential hazards. A large number of accidents such as explosions or fires have been reported, rendering it necessary to conduct a number of qualitative and quantitative risk assessments for HRSs. Current safety codes and technical standards related to Japanese HRSs have been established based on the results of a qualitative risk assessment and quantitative effectiveness validation of safety measures over ten years ago. In the last decade, there has been much development in the technologies of the components or facilities used in domestic HRSs and much operational experience as well as knowledge to use hydrogen in HRSs safely have been gained through years of commercial operation. The purpose of the present study is to conduct a quantitative risk assessment (QRA) of the latest HRS model representing Japanese HRSs with the most current information and to identify the most significant scenarios that pose the greatest risks to the physical surroundings in the HRS model. The results of the QRA show that the risk contours of 10^?3 and 10^?4 per year were confined within the HRS boundaries, whereas the risk contours of 10^?5 and 10^?6 per year are still present outside the HRS. Comparing the breakdown of the individual risks (IRs) at the risk ranking points, we conclude that the risk of jet fire demonstrates the highest contribution to the risks at all of the risk ranking points and outside the station. To reduce these risks and confine the risk contour of 10^?6 per year within the HRS boundaries, it is necessary to consider risk mitigation measures for jet fires.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.