Dilatancy relation for overconsolidated clay

A distinct feature of overconsolidated (OC) clays is that their dilatancy behavior is dependent on the degree of overconsolidation. Typically, a heavily OC clay shows volume expansion, whereas a lightly OC clay exhibits volume contraction when subjected to shear. Proper characterization of the stress-dilatancy behavior proves to be important for constitutive modeling of OC clays. This paper presents a dilatancy relation in conjunction with a bounding surface or subloading surface model to simulate the behavior of OC clays. At the same stress ratio, the proposed relation can reasonably capture the relatively more dilative response for clay with a higher overconsolidation ratio (OCR). It may recover to the dilatancy relation of a modified Cam-clay (MCC) model when the soil becomes normally consolidated (NC). A demonstrative example is shown by integrating the dilatancy relation into a bounding surface model. With only three extra parameters in addition to those in the MCC model, the new model and the proposed dilatancy relation provide good predictions on the behavior of OC clay compared with experimental data

The Neural Networks Based Needle Detection for Medical Retinal Surgery

In recent years, deep learning technology has developed rapidly, and the application of deep neural networks in the medical image processing field has become the focus of the spotlight. This paper aims to achieve needle position detection in medical retinal surgery by adopting the target detection algorithm based on YOLOv5 as the basic deep neural network model. The state-of-the-art needle detection approaches for medical surgery mainly focus on needle structure segmentation. Instead of the needle segmentation, the proposed method in this paper contains the angle examination during the needle detection process. This approach also adopts a novel classification method based on the different positions of the needle to improve the model. The experiments demonstrate that the proposed network can accurately detect the needle position and measure the needle angle. The performance test of the proposed method achieves 4.80 for the average Euclidean distance between the detected tip position and the actual tip position. It also obtains an average error of 0.85 degrees for the tip angle across all test sets

Investigation of a refrigeration system based on combined supercritical CO2 power and transcritical CO2 refrigeration cycles by waste heat recovery of engine

The majority of the energy in the fuel burned in the internal combustion engines is lost in the form of waste heat. To address this issue, waste heat recovery technology has been proposed to increases the overall efficiency of engine. This paper investigates a heat driven cooling system based on a supercritical CO2 (S-CO2) power cycle integrated with a transcritical CO2 (T-CO2) refrigeration cycle, aiming to provide an alternative to the vapour absorption cooling system. The combined system is proposed to produce cooling for food preservation on a refrigerated truck by waste heat recovery of engine. In this system, the S-CO2 absorbs heat from the exhaust gas and the generated power in the expander is used to drive the compressors in both S-CO2 power cycle and T-CO2 refrigeration cycle. Unlike the bulky vapour absorption cooling system, both power plant and vapour compression refrigerator can be scaled down to a few kilo Watts, opening the possibility for developing small-scale waste heat driven cooling system that can be widely applied for waste heat recovery from IC engines of truck, ship and trains.A new layout sharing a common cooler is also studied. The results suggest that the concept of S-CO2/T-CO2 combined cycle sharing a common cooler has comparable performance and it is thermodynamically feasible. The heat contained in exhaust gas is sufficient for the S-CO2/T-CO2 combined system to provide enough cooling for refrigerated truck cabinet whose surface area is more than 105 m2

Judicial Intelligent Assistant System: Extracting Events from Divorce Cases to Detect Disputes for the Judge

In formal procedure of civil cases, the textual materials provided by different parties describe the development process of the cases. It is a difficult but necessary task to extract the key information for the cases from these textual materials and to clarify the dispute focus of related parties. Currently, officers read the materials manually and use methods, such as keyword searching and regular matching, to get the target information. These approaches are time-consuming and heavily depending on prior knowledge and carefulness of the officers. To assist the officers to enhance working efficiency and accuracy, we propose an approach to detect disputes from divorce cases based on a two-round-labeling event extracting technique in this paper. We implement the Judicial Intelligent Assistant (JIA) system according to the proposed approach to 1) automatically extract focus events from divorce case materials, 2) align events by identifying co-reference among them, and 3) detect conflicts among events brought by the plaintiff and the defendant. With the JIA system, it is convenient for judges to determine the disputed issues. Experimental results demonstrate that the proposed approach and system can obtain the focus of cases and detect conflicts more effectively and efficiently comparing with existing method.Comment: 20 page

ScalAna: Automating Scaling Loss Detection with Graph Analysis

Scaling a parallel program to modern supercomputers is challenging due to inter-process communication, Amdahl's law, and resource contention. Performance analysis tools for finding such scaling bottlenecks either base on profiling or tracing. Profiling incurs low overheads but does not capture detailed dependencies needed for root-cause analysis. Tracing collects all information at prohibitive overheads. In this work, we design ScalAna that uses static analysis techniques to achieve the best of both worlds - it enables the analyzability of traces at a cost similar to profiling. ScalAna first leverages static compiler techniques to build a Program Structure Graph, which records the main computation and communication patterns as well as the program's control structures. At runtime, we adopt lightweight techniques to collect performance data according to the graph structure and generate a Program Performance Graph. With this graph, we propose a novel approach, called backtracking root cause detection, which can automatically and efficiently detect the root cause of scaling loss. We evaluate ScalAna with real applications. Results show that our approach can effectively locate the root cause of scaling loss for real applications and incurs 1.73% overhead on average for up to 2,048 processes. We achieve up to 11.11% performance improvement by fixing the root causes detected by ScalAna on 2,048 processes.Comment: conferenc

Collaborative Heterogeneity-Aware OS Scheduler for Asymmetric Multicore Processors

Funding: This work is supported in part by the China Postdoctoral Science Foundation (Grant No. 2020TQ0169), the ShuiMu Tsinghua Scholar fellowship (2019SM131), National Key R&D Program of China (2020AAA0105200), National Natural Science Foundation of China (U20A20226), Beijing Natural Science Foundation (4202031), Beijing Academy of Artificial Intelligence BAAI), the UK EPSRC grants Discovery: Pattern Discovery and Program Shaping for Manycore Systems (EP/P020631/1). This work is also supported by the Royal Academy of Engineering under the Research Fellowship scheme.Asymmetric multicore processors (AMP) offer multiple types of cores under the same programming interface. Extracting the full potential of AMPs requires intelligent scheduling decisions, matching each thread with the right kind of core, the core that will maximize performance or minimize wasted energy for this thread. Existing OS schedulers are not up to this task. While they may handle certain aspects of asymmetry in the system, none can handle all runtime factors affecting AMPs for the general case of multi-threaded multi-programmed workloads. We address this problem by introducing COLAB, a general purpose asymmetry-aware scheduler targeting multi-threaded multi-programmed workloads. It estimates the performance and power of each thread on each type of core and identifies communication patterns and bottleneck threads. With this information, the scheduler makes coordinated core assignment and thread selection decisions that still provide each application its fair share of the processor’s time. We evaluate our approach using both the GEM5 simulator on four distinct big.LITTLE configurations and a development board with ARM Cortex-A73/A53 processors and mixed workloads composed of PARSEC and SPLASH2 benchmarks. Compared to the state-of-the art Linux CFS and AMP-aware schedulers, we demonstrate performance gains of up to 25% and 5% to 15% on average,together with an average 5% energy saving depending on the hardware setup.PostprintPeer reviewe

Influence of coal characteristics on laser-induced plasmas

peer reviewedEight kinds of typical coal samples were chosen for studying the influence of coal characteristics on laser—induced plasmas．Element analysis and industry analysis were carried out for every sample．Experimental study on the interaction between laser and different coal samples was completed，and factors affecting laser plasma were analyzed，such as coal moisture and coal dust．The experiment result indicates that the coal samples with different coalification degrees have different plasma time—resolved spectral characteristics，all of them tend to rise at the beginning of plasma formation (< 1us)，then with the decay of plasmas emission．they tend to decrease in about 1us，while secondary ionization occurs in highly coalificated coals after 2 us．The plasma temperature differs from one kind to another，the higher the coalification degree is，the higher the plasma temperature will be

Modeling seismic wave propagation in the Loess Plateau using a viscoacoustic wave equation with explicitly expressed quality factor

The thick Quaternary loess on the Loess Plateau of China produces strong seismic attenuation, resulting in weak reflections from subsurface exploration targets. Accurately simulating seismic wavefield in the Loess Plateau is important for guiding subsequent data processing and interpretation. We present a 2D/3D wavefield simulation method for the Loess Plateau using a viscoacoustic wave equation with explicitly expressed quality factor. To take into account the effect of irregular surface, we utilize a vertically deformed grid to represent the topography, and solve the viscoacoustic wave equation in a regular computational domain that conforms to topographic surface. Grid deformation introduces the partial derivatives such as ∂vx/∂z and ∂vy/∂z in the wave equation, which is difficult to be accurately computed using traditional staggered-grid finite-difference method. To mitigate this issue, a finite-difference scheme based on a fully staggered-grid is adopted to solve the viscoacoustic wave equation. Numerical experiments for a simple layer model and 2D/3D realistic Loess Plateau models demonstrate the feasibility and adaptability of the proposed method. The 3D modeling results show comparable amplitude and waveform characteristics to the field data acquired from the Chinese Loess Plateau, suggesting a good performance of the proposed modeling method