Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This st...Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.展开更多
Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving.This paper presents a novel 3D object detector...Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving.This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively.Using 2D region proposals in an RGB image,this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network(FPS-Net)and feature extraction network(FE-Net).Subsequently,the encoder-decoder network(ED-Net)implements 3D-oriented bounding box(OBB)regression.Meanwhile,the adaptive least square regression(ALSR)method is proposed to split 3D OBB.Finally,the reduced OBB intersection test is carried out to detect traffic accidents via separating surface theorem(SST).In the experiments of KITTI benchmark,our proposed 3D object detector outperforms other state-of-theartmethods.Meanwhile,collision detection algorithm achieves the satisfactory performance of 91.8%accuracy on our SHTA dataset.展开更多
According to the physical and chemical characteristics of superfine powder extinguishing agent,three test methods are selected to measure the flow ability.By studying and comparing various test methods,apparatus and c...According to the physical and chemical characteristics of superfine powder extinguishing agent,three test methods are selected to measure the flow ability.By studying and comparing various test methods,apparatus and conditions,the optimum method and conditions to test flow property of superfine powder extinguishing agent are confirmed.展开更多
In the present study,a multi-objective optimization of a flow straightener in a firefighting water cannon is performed by using the surrogate modeling and a hybrid multi-objective genetic algorithm to increase the jet...In the present study,a multi-objective optimization of a flow straightener in a firefighting water cannon is performed by using the surrogate modeling and a hybrid multi-objective genetic algorithm to increase the jet range of the water cannon.Based on analysis using the three-dimensional Reynolds-averaged Navier-Stokes equations,the optimization is carried with a surrogate model and the radial basis neural network.Three geometric design variables,i.e.,the lengt扎 the thickness of the blade,and the radius of the outer pipe of the flow straightener,are selected for the optimization.The pressure drop through the water can non and the area-averaged turbulent kinetic energy at the outlet of the water cannon,which are closely related to the jet range of the water cannon,are selected as the objective functions to be minimized.The design space is determined through a parametric study,and the Latin hypercube sampling method is used to select the design points in the design space.The Pareto-optimal solutions are obtained through the optimization.Five representative Pareto-optimal solutions are selected to study the trade-off between two objectives.展开更多
文摘Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.
基金National Natural Science Foundation of China(No.51805312)in part by Shanghai Sailing Program(No.18YF1409400)+4 种基金in part by Training and Funding Program of Shanghai College young teachers(No.ZZGCD15102)in part by Scientific Research Project of Shanghai University of Engineering Science(No.2016-19)in part by Science and Technology Commission of Shanghai Municipality(No.19030501100)in part by the Shanghai University of Engineering Science Innovation Fund for Graduate Students(No.18KY0613)in part by National Key R&D Program of China(No.2016YFC0802900).
文摘Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving.This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively.Using 2D region proposals in an RGB image,this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network(FPS-Net)and feature extraction network(FE-Net).Subsequently,the encoder-decoder network(ED-Net)implements 3D-oriented bounding box(OBB)regression.Meanwhile,the adaptive least square regression(ALSR)method is proposed to split 3D OBB.Finally,the reduced OBB intersection test is carried out to detect traffic accidents via separating surface theorem(SST).In the experiments of KITTI benchmark,our proposed 3D object detector outperforms other state-of-theartmethods.Meanwhile,collision detection algorithm achieves the satisfactory performance of 91.8%accuracy on our SHTA dataset.
文摘According to the physical and chemical characteristics of superfine powder extinguishing agent,three test methods are selected to measure the flow ability.By studying and comparing various test methods,apparatus and conditions,the optimum method and conditions to test flow property of superfine powder extinguishing agent are confirmed.
基金the National Natural Science Foundation of China (Grant No.51379090).
文摘In the present study,a multi-objective optimization of a flow straightener in a firefighting water cannon is performed by using the surrogate modeling and a hybrid multi-objective genetic algorithm to increase the jet range of the water cannon.Based on analysis using the three-dimensional Reynolds-averaged Navier-Stokes equations,the optimization is carried with a surrogate model and the radial basis neural network.Three geometric design variables,i.e.,the lengt扎 the thickness of the blade,and the radius of the outer pipe of the flow straightener,are selected for the optimization.The pressure drop through the water can non and the area-averaged turbulent kinetic energy at the outlet of the water cannon,which are closely related to the jet range of the water cannon,are selected as the objective functions to be minimized.The design space is determined through a parametric study,and the Latin hypercube sampling method is used to select the design points in the design space.The Pareto-optimal solutions are obtained through the optimization.Five representative Pareto-optimal solutions are selected to study the trade-off between two objectives.
