bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating InfluxDB and ClickHouse database technologies for improvements of the ATLAS operational monitoring data archiving
Authors: Vasile Matei-Eugen , Avolio Giuseppe , Soloviev Igor
Published: July 2020

The Trigger and Data Acquisition system of the ATLAS experiment at the Large Hadron Collider at CERN is composed of a large number of distributed hardware and software components which provide the data-taking functionality of the overall system. During data-taking, huge amounts of operational data are created in order to constantly monitor the system. The Persistent Back-End for the ATLAS Information System of TDAQ (P-BEAST) is a system based on a custom-built timeseries database. It is used to archive and retrieve any operational monitoring data for the applications requesting it. P-BEAST stores about 18 TB of highly compacted and compressed raw monitoring data per year. Since P-BEAST’s creation, several promising database technologies for fast access to time-series have become available. InfluxDB and ClickHouse were the most promising candidates for improving the performance and functionality of the current implementation of P-BEAST. This paper presents a short description of main features of both technologies and a description of the tests ran on both database systems. Then, the results of the performance testing performed using a subset of archived ATLAS operational monitoring data are presented and compared.
ELisA: the ATLAS logbook facility extensions
Authors: Corso-Radu Alina , Avolio Giuseppe
Published: July 2020

Information concerning the operation, configuration and behavior of the ATLAS experiment needs to be reported, gathered and shared reliably with the whole ATLAS community which comprises over three thousand scientists geographically distributed all over the world. To provide such functionality, a logbook facility, Electronic Logbook for the information storage of ATLAS (ELisA), has been developed and actively used since the beginning of the LHC Run 2 period. The facility includes a user-friendly web interface to browse activity logs and to report on system operations with a configurable email notification system; a RESTful API used programmatically by other tools and services of the data acquisition infrastructure, and a set of client API libraries and utilities to help user’s interaction with the REST API. Given its generic configuration capabilities, the ELisA facility has been recently deployed as a stand-alone logbook for other projects such as the commissioning of different sub-detectors and the offline assessment of data-quality. To ease this operation and to potentially extend ELisA usage to other projects, an extension of the database backend support is being implemented to reduce the dependency on the ORACLE database for the logbook deployment. Also, the deployment process of the logbook is being improved. This contribution will present the status of the logbook facility as well as the extensions and improvements implemented to ease the logbook portability to other projects.*
CMS Software and Offline preparation for future runs
Authors: Boccali Tommaso
Published: July 2020

The next LHC Runs, nominally Run III and Run IV, pose problems to the offline and computing systems in CMS. Run IV in particular will need completely different solutions, given the current estimates of LHC conditions and Trigger estimates. We report on the R&D process CMS has established, in order to gain insight on the needs and the possible solutions for the 2020+ CMS computing.
High-performance, deep neural networks with sub-microsecond latency on FPGAs for trigger applications
Authors: Nottbeck Noel , Schmitt Christian , Büscher Volker
Published: July 2020

Modern high-end FPGAs, as they are often used for hardware-level trigger applications, offer enough arithmetic performance to include artificial neural networks of considerable size into such systems. Yet, there are only very few examples of the inclusion of ANNs into high-performance hardware triggers, which is especially due to the complex and time-consuming development for FPGAs, and the need for an optimized design in order to make efficient use of the FPGA capabilities. We developed a library that provides three types of layers: Fully-connected dense layers, as well as 2D multi-channeled convolution and maximum pooling layers. For maximum design control, these were designed with VHDL and optimized for the specific data flow and control requirements of each layer type. By that, it was possible to obtain multiple hundred MHz processing frequency and have only little resource overhead beyond what is required for the actual computation for the individual layers. Furthermore, we created a Python-based toolkit that builds on these layer implementations to make it possible to take a trained network from the Keras framework and create the FPGA firmware and initialization data without requirement of in-depth understanding by the user. The resulting (deep) network designs can process data coming in at multiple ten MHz at multiple hundred MHz processing frequency and latencies ranging from tens to few hundreds of nanoseconds, depending on the network size.
A new scheduling algorithm for the LHCb upgrade trigger application
Authors: Govorkova Ekaterina , Hasse Christoph , Matev Rosen , Nolte Niklas , Ponce Sebastien , Raven Gerhard , Stahl Sascha
Published: July 2020

During Run3 of the LHC the LHCb detector will process a 30 MHz event rate with a full detector readout followed by a software trigger. To deal with the increased computational requirements, the software framework is reviewed and optimized on a large scale. One challenge is the efficient scheduling of O(103)-O(104) algorithms in the High Level Trigger (HLT) application. This document describes the design of a new algorithm scheduler which allows for static-order intra-event scheduling with minimum complexity while still providing the required flexibility.
Federation of compute resources available to the German CMS community
Authors: von Cube R F , Giffels M , Heidecker C , Quast G , Sauter M B , Schnepf M J
Published: July 2020

The German CMS community (DCMS) as a whole can benefit from the various compute resources, available to its different institutes. While Grid-enabled and National Analysis Facility resources are usually shared within the community, local and recently enabled opportunistic resources like HPC centers and cloud resources are not. Furthermore, there is no shared submission infrastructure available.

Via HTCondor’s [1] mechanisms to connect resource pools, several remote pools can be connected transparently to the users and therefore used more efficiently by a multitude of user groups. In addition to the statically provisioned resources, also dynamically allocated resources from external cloud providers as well as HPC centers can be integrated. However, the usage of such dynamically allocated resources gives rise to additional complexity. Constraints on access policies of the resources, as well as workflow necessities have to be taken care of. To maintain a well-defined and reliable runtime environment on each resource, virtualization and containerization technologies such as virtual machines, Docker, and Singularity, are used.
The ATLAS EventIndex and its evolution towards Run 3
Authors: Villaplana Perez M , Alexandrov E , Aleksandrov I , Baranowski Z , Barberis D , Dimitrov G , Fernandez Casani A , Gallas E , Garcia Montoro C , Gonzalez de la Hoz S , Hrivnac J , Alexander I , Kazymov A , Mineev M , Prokoshin F , Rybkin G , Sanchez J , Salt J , Vasileva P T
Published: July 2020

The ATLAS experiment has produced hundreds of petabytes of data and expects to have one order of magnitude more in the future. This data are spread among hundreds of computing Grid sites around the world. The EventIndex is the complete catalogue of all ATLAS events, real and simulated, keeping the references to all permanent files that contain a given event in any processing stage. It provides the means to select and access event data in the ATLAS distributed storage system, and provides support for completeness and consistency checks and trigger and offline selection overlap studies. The EventIndex employs various data handling technologies like Hadoop and Oracle databases, and it is integrated with other parts of the ATLAS distributed computing infrastructure, including systems for data, metadata, and production management. The project has been in operation since the start of LHC Run 2 in 2015, and it is in permanent development in order to satisfy the production and analysis demands and follow technology evolution. The main data store in Hadoop, based on MapFiles and HBase, has worked well during Run 2 but new solutions are being explored for the future. This paper reports on the current system performance and on the studies of a new data storage prototype that can carry the EventIndex through Run 3.
CernVM-FS Container Image Integration
Authors: Mosciatti Simone , Blomer Jakob , Ganis Gerardo , Popescu Radu
Published: July 2020

Linux containers have gained widespread use in high energy physics, be it for services using container engines such as containerd/kubernetes, for production jobs using container engines such as Singularity or Shifter, or for development workflows using Docker as a local container engine. Thus the efficient distribution of the container images, whose size usually ranges from a few hundred megabytes to a few tens of gigabytes, is becoming a pressing concern. Because container images show similar characteristics than scientific application stacks, unpacking the images in CernVM-FS can remedy the distribution issues provided that the container engine at hand is able to use such unpacked images from CernVM-FS. In this contribution, we willl report on recent advances in the integration of Singularity, Docker, and containerd with CernVM-FS. We show improvements in the publishing of container images from a Docker registry that rely on new means of directly ingesting image tarballs. Well also show a repository file system structure for storing container images that are optimized for storing both container engines using flat root file systems (Singularity) as well as container engines using layers (containerd, Docker). To evaluate the benefits of our approach, we show concrete use cases and figures for production and development images from LHC experiments stored in the recently created unpacked.cern.ch repository.
Generative Adversarial Networks for fast simulation
Authors: Carminati Federico , Khattak Gulrukh , Loncar Vladimir , Nguyen Thong Q , Pierini Maurizio , Brito Da Rocha Ricardo , Samaras-Tsakiris Konstantinos , Vallecorsa Sofia , Vlimant Jean-Roch
Published: July 2020

Deep Learning techniques are being studied for different applications by the HEP community: in this talk, we discuss the case of detector simulation. The need for simulated events, expected in the future for LHC experiments and their High Luminosity upgrades, is increasing dramatically and requires new fast simulation solutions. Here we present updated results on the development of 3DGAN, one of the first examples using three-dimensional convolutional Generative Adversarial Networks to simulate high granularity electromagnetic calorimeters. In particular, we report on two main aspects: results on the simulation of a more general, realistic physics use case and on data parallel strategies to distribute the training process across multiple nodes on public cloud resources.
Boosting Performance of Data-intensive Analysis Workflows with Distributed Coordinated Caching
Authors: Heidecker C , von Cube R F , Giffels M , Quast G , Sauter M , Schnepf M J
Published: July 2020

Data-intensive end-user analyses in high energy physics require high data throughput to reach short turnaround cycles. This leads to enormous challenges for storage and network infrastructure, especially when facing the tremendously increasing amount of data to be processed during High-Luminosity LHC runs. Including opportunistic resources with volatile storage systems into the traditional HEP computing facilities makes this situation more complex.

Bringing data close to the computing units is a promising approach to solve throughput limitations and improve the overall performance. We focus on coordinated distributed caching by coordinating workows to the most suitable hosts in terms of cached files. This allows optimizing overall processing efficiency of data-intensive workows and efficiently use limited cache volume by reducing replication of data on distributed caches.

We developed a NaviX coordination service at KIT that realizes coordinated distributed caching using XRootD cache proxy server infrastructure and HTCondor batch system. In this paper, we present the experience gained in operating coordinated distributed caches on cloud and HPC resources. Furthermore, we show benchmarks of a dedicated high throughput cluster, the Throughput-Optimized Analysis-System (TOpAS), which is based on the above-mentioned concept.
A hybrid deep learning approach to vertexing
Authors: Fang Rui , Schreiner Henry F , Sokoloff Michael D , Weisser Constantin , Williams Mike
Published: July 2020

During the LHC Run 3, the instantaneous luminosity received by LHCb will be increased going from 1.1 to 5.6 expected visible Primary Vertices (PVs) per event. To face this challenge, the LHCb detector will be upgraded and will adopt a purely software trigger. This has fueled increased interest in alternative highly-parallel and GPU friendly algorithms for tracking and reconstruction. We will present a novel prototype algorithm for vertexing in the LHCb upgrade conditions. We use a custom kernel to transform the sparse 3D space of hits and tracks into a dense 1D dataset, and then apply Deep Learning techniques to find PV locations. By training networks on our kernels using several Convolutional Neural Network layers, we have achieved better than 90% efficiency with no more than 0.2 False Positives (FPs) per event. Beyond its physics performance, this algorithm also provides a rich collection of possibilities for visualization and study of 1D convolutional networks. We will discuss the design, performance, and future potential areas of improvement and study, such as possible ways to recover the full 3D vertex information.
Particle Generative Adversarial Networks for full-event simulation at the LHC and their application to pileup description
Authors: Arjona Martínez Jesus , Nguyen Thong Q , Pierini Maurizio , Spiropulu Maria , Vlimant Jean-Roch
Published: July 2020

We investigate how a Generative Adversarial Network could be used to generate a list of particle four-momenta from LHC proton collisions, allowing one to define a generative model that could abstract from the irregularities of typical detector geometries. As an example of application, we show how such an architecture could be used as a generator of LHC parasitic collisions (pileup). We present two approaches to generate the events: unconditional generator and generator conditioned on missing transverse energy. We assess generation performances in a realistic LHC data-analysis environment, with a pileup mitigation algorithm applied.
Tag-based Analysis at the BESIII Experiment
Authors: Deng Z Y , Zou J H , Sun S S , Liu B J , Wang L , Shi J Y , Xiong X A , Zhang S F
Published: July 2020

As more and more data is accumulated from BESIII detector, the reduction of the CPU time of data processing procedures is significant for the experiment to get physics results efficiently with limited hardware resources. In this study, we designed a tag-based analysis method in BESIII offline software system. Typical physics analysis results show the tag-based analysis with reformed DST file can reduce the jobs running time to about 1/10, with high CPU efficiency and low read throughput, without inducing additional disk space occupation.
Digitization of Cylindrical GEM Detector
Authors: Zhao Jingyi , Miao Nannan , Wu Linghui , Wang Liangliang , Sun Tong , Huang Zhen , Mitchell Ryan , Li Weiguo , Liu Huaimin , Lou Xinchou , Sun Shengsen , Yuan Ye , Zhang Yao
Published: July 2020

The BESIII inner drift chamber is suffering from aging effect. Cylindrical Gas Electron Multiplier Inner Tracker (CGEM-IT) is considered as one of the upgrade candidates. A simulation study with Garfield++ program has been performed to understand the drift behaviour and to build a full digitization model. Parameters related to Lorentz angle, diffusion effect, drift time, multiplication and induction are obtained from the Garfield++ simulation. A preliminary digitization model is implemented in the BESIII Offline Software System (BOSS) based on those parameters.
Meta-Learning for Artificial Neural Network Hyper-Parameter Optimization for CERN CMS Offline Data Certification
Authors: Stankevicius Mantas , Marcinkevicius Virginijus , Rapsevicius Valdas
Published: July 2020

The Compact Muon Solenoid (CMS) is one of the general-purpose detectors at the CERN Large Hadron Collider (LHC) which collects enormous amounts of physics data. Before the final physics analysis can proceed, data has to be checked for quality (certified) by passing a number of automatic (like physics objects reconstruction, histogram preparation) and manual (checking, comparison and decision making) steps. Last manual step of decision making is very important, error-prone and demands a lot of manpower. Decision making (certification) is currently under active research in computer science for automation by applying recent advancements from computer science, specifically, machine learning (ML).

Ultimately, CMS data certification is a binary classification task where various ML techniques are being investigated for applicability. Just like in any other ML task the hyperparameter tuning is a difficult problem, there is no golden rule and each use case is different. This study explored meta-learning applicability, it is a hyper-parameters finding technique where algorithm learns hyper-parameters from previous training experiments. An Evolutionary genetic algorithm has been used to tune hyper-parameters of a neural network, like number of hidden layers, number of neurons per layer, activation functions, dropouts, training batch size and optimizer. Initially, the genetic algorithm takes manually specified set of hyper-parameters and then evolves towards the near-optimal solution. Genetic stochastic operators, crossover and mutation, were applied to avoid local optimal solutions.

This study shows that by carefully seeding the initial solution the optimal is likely to be found. The proposed solution has improved AUC score of neural network used for CERN CMS data certification. Similar algorithm can be applied for other machine learning models for hyper-parameter optimization.
Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs
Authors: Hagen A , Church E , Strube J , Bhattacharya K , Amatya V
Published: July 2020

Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab [1], feature large, high fidelity event images. Deep learning techniques have been extremely successful in classification tasks of photographs, but their application to LArTPC event images is challenging, due to the large size of the events. Events in these detectors are typically two orders of magnitude larger than images found in classical challenges, like recognition of handwritten digits contained in the MNIST database or object recognition in the ImageNet database. Ideally, training would occur on many instances of the entire event data, instead of many instances of cropped regions of interest from the event data. However, such efforts lead to extremely long training cycles, which slow down the exploration of new network architectures and hyperparameter scans to improve the classification performance. We present studies of scaling a LArTPC classification problem on multiple architectures, spanning multiple nodes. The studies are carried out on simulated events in the MicroBooNE detector. We emphasize that it is beyond the scope of this study to optimize networks or extract the physics from any results here. Institutional computing at Pacific Northwest National Laboratory and the SummitDev machine at Oak Ridge National Laboratory’s Leadership Computing Facility have been used. To our knowledge, this is the first use of state-of-the-art Convolutional Neural Networks for particle physics and their attendant compute techniques onto the DOE Leadership Class Facilities. We expect benefits to accrue particularly to the Deep Underground Neutrino Experiment (DUNE) LArTPC program, the flagship US High Energy Physics (HEP) program for the coming decades.
Deep learning for Directional Dark Matter search
Authors: Golovatiuk Artem , De Lellis Giovanni , Ustyuzhanin Andrey
Published: July 2020

We provide an algorithm for detection of possible dark matter particle interactions recorded within NEWSdm detector. The NEWSdm (Nuclear Emulsions for WIMP Search directional measure) is an underground Direct detection Dark Matter search experiment. The usage of recent developments in the nuclear emulsions allows probing new regions in the WIMP parameter space. The directional approach, which is the key feature of the NEWSdm experiment, gives the unique chance of overcoming the neutrino floor. Deep Neural Networks were used for separation between potential DM signal and various classes of background. In this paper, we present the usage of deep 3D Convolutional Neural Networks to take into account the physical peculiarities of the datasets and report the achievement of the required 104 background rejection power.
Analyzing the streamflow-sediment links of three major river basins in India using multifractal theory
Authors: Adarsh S , Watorek Marcin
Published: July 2020

This study investigated the cross-correlation between daily streamflow and total suspended sediment (TSS) data of 65 gauging stations located in three major river basins in a multifractal perspective. The novel Multifractal Cross Correlation Analysis (MFCCA) method of cross correlation studies is used to analyze the streamflow-sediment links of Krishna, Godavari and Mahanadi basins. The results showed that for the records of a particular station, the joint persistence of streamflow and TSS is approximately the mean of the persistence of individual series. The streamflow displayed higher persistence than TSS in 60 % of the stations while in majority of stations of Godavari basin the trend was opposite. The annual cross correlation is higher than overall cross correlation in majority of stations but at these time scales strength of their association differs with river basin.
Assessment of meteorological droughts over Hoshangabad district, India
Authors: Swain Sabyasachi , Kumar Mishra Surendra , Pandey Ashish
Published: July 2020

In this study, the meteorological drought characteristics (severity, frequency, and persistence) over the Hoshangabad district, Madhya Pradesh, India are analyzed. The percent departure from mean (PDM) is employed to describe the drought characteristics, considering the monthly rainfall data for the duration of 62 years (1951-2012). Rainfall during monsoon season contributes over 95% of the annual rainfall and thus, only monsoon season is considered for identifying the drought years. The entire duration of 62 years was divided into two epochs of 31 years i.e. 1951-1981 and 1982-2012. The results revealed that the rainfall over the district possesses remarkable inter-annual variability. The district is prone to droughts with a frequency of once in four years. More importantly, the comparative assessment of two epochs indicates an increase in frequency, severity, and persistence of droughts in the latter epoch. The frequency of droughts has tripled in 1982-2012 as compared to 1951-1981. Since Hoshangabad is a monsoon-dominated district with high agricultural importance, proper management strategies need to be devised to minimize the harmful consequences of droughts.
Nonlinear finite element modelling of concrete columns confined with textile reinforced mortar
Authors: John Shaise K , Nadir Yashida , Girija K
Published: July 2020

Textile reinforced mortar (TRM) is an innovative material developed to overcome the limitations of fibre reinforced polymer (FRP). It consists of high strength textile fibre mesh embedded in cementitious binder which is organic in nature and compatible with concrete substrate. This paper presents the development of a finite element model for confinement of concrete columns using TRM. Concrete damaged plasticity model was used to represent the behaviour of TRM. The model accounts for nonlinear material behaviour in concrete core and mortar. The model was validated against experimental result from literature. Maximum divergence between experimental and numerical results was 5%. Following the validation, the developed model was used to carry out parametric studies on circular and square column confinement. The thickness of mortar layer, cross section shape of the core and corner radius of square column were considered in the study to gain a profound knowledge of the confinement and to study its influence on the behaviour of confined concrete column.
A review on the deterioration of cement-based materials in ammonium salt solutions
Authors: Babu Sheba , Ramaswamy K P , Nazeer M
Published: July 2020

It is essential to understand the durability aspects as the cementitious systems exposed to agricultural zones, fertilizer plants, waste waters, mining and industrial applications can be subjected to chemical attack by ammonium based compounds. This paper reviews the different mechanisms of deterioration of cement composites on exposure to different ammonium compounds namely ammonium sulphate, nitrate and chloride. The magnitude and mechanism of degradation follows different trends depending on the type of anion associated with the ammonium salts. The principle process involved in the deterioration of cementitious systems in the presence of ammonium compounds is the chemical reaction of portlandite with the anion of the ammonium salts. Generally the interaction of ammonium salts with cement based materials results in decalcification, leaching and/or expansion accompanied by strength loss. The presence of Supplementary Cementitious Materials (SCMs) along with cement reduces the amount of portlandite which may be attributed to the dilution of cement component or increased pozzolanic activity, resulting in the production of additional or secondary C-S-H gel. It is observed that the incorporation of SCMs is found to have low penetrability, thus capable of controlling the degradation process upon exposure to ammonium based salt solutions.
A critical review on the durability of geopolymer composites in acidic environment
Authors: Ajay Athira , Ramaswamy K P , Thomas Anu V
Published: July 2020

Deterioration of concrete in acidic environments result in premature degradation in terms of microstructural alteration of phases leading to mass changes, weakening of mechanical properties, increase in porosity due to calcium leaching etc. Industries are found to dispose acidic effluents directly into the environment without proper treatments. Again, these acids can be organic as well as inorganic acids. Organic acids unlike inorganic acids are found to be weak acids due to their partly dissociative nature. The mechanism of acid attack varies based on the acid type and the characteristics of the calcium salt that are formed. Conventional concrete made with Ordinary Portland Cement (OPC) are not resistant to acids. Also, as we strive towards sustainable development, alkali activated or geopolymer concrete has started to gain attention as it is found to have better mechanical properties and durability comparing to conventional concrete. This paper reviews the damage mechanisms of sulphuric acid, citric acid, nitric acid and acetic acid on the alkali activated binders.
A critical review on the effect of organic acids on cement-based materials
Authors: Mariam Ninan Chinnu , Ajay Athira , Ramaswamy K P , Thomas Anu V , Bertron Alexandra
Published: July 2020

Ingression of acids into concrete structure arrests its long-term durability by the progressive degradation of the highly alkaline cementitious materials. Acid attack results in the decalcification of hydration products leading to higher inherent porosity and both micro-macro cracks, providing a path for the passage of aggressive ions into the interior of concrete. Amplification of agriculture and food industries such as the breeding, dairy or sugar industries produce large quantities of effluents that are the major sources of organic acids. These effluents have complex acidic compositions leading to serious degradation of structures made for their production, collection, storage and treatment. New binder systems that are capable of proposing extensive long term durability in aggressive acidic environment and also being a sustainable option need to be evolved. From earlier studies, application of various binder systems containing materials such as fly ash, ground granulated blast furnace slag, silica fume, bagasse ash etc. has an influence on the hydration products, micro-structural and macro-structural changes in cement-based materials when subjected to aggressive acidic media, thus enhancing the performance and durability of concrete structures. This paper outlines the basic mechanism of organic acid attack and highlights the influence of various binder systems on the alteration of degradation kinetics when exposed to various organic acids.
Preparation of magnetic composite materials and Its Application in Heavy metal wastewater Treatment
Authors: Zeng Qian , Lei Zengjiang , Yang Jinhui , Ma Hongda , Luo Yi
Published: July 2020

The heavy discharge of industrial wastewater containing heavy metal ions has caused serious pollution to water bodies and soils. Due to the heavy toxicity and biodegradability of heavy metals, the polluted water bodies have serious consequences for humans, animals and plants. The surface of magnetic materials is easy to be functionally modified and has good magnetic sensitivity. However, some single magnetic materials have problems such as easy aggregation and difficult to disperse and separate, which limits their application. And by combining a single magnetic material with other materials, colleagues who can play their advantages can avoid the defects. The magnetic composite material changes the movement of heavy metal ions in sewage to achieve the effect of adsorption under the action of a magnetic field. It has the advantages of wide source of materials, simple preparation method, efficient adsorption, and repeated use. With a wide range of applications, the research and development of magnetic composite materials has also received widespread attention. This article gives a comprehensive overview of the structural properties of different magnetic composites and their adsorption effects on heavy metal ions, in order to provide research directions and new ideas for magnetic composites on heavy metal ion adsorption.
Study on Equivalent Transformation of Structural Design Parameters Based on Overseas Codes
Authors: Ren Hongmei , Peng Gongsheng
Published: July 2020

With the development of the Belt and Road Initiative and economic globalization, we are going deep into the world. China’s overseas engineering projects are increasing day by day, which puts forward higher requirements for structural designers. While skillfully using domestic codes and standards, designers must also understand the design codes of overseas project locations, and master the mutual transformation of basic design parameters at home and abroad. Taking a project in Pakistan as an example, this paper expounds in detail how to convert the basic design parameters of Pakistan into the design parameters corresponding to the domestic specifications, with a view to providing reference for colleagues to carry out overseas project design.
Research on Load Checking of In-service Pressure Vessel Nozzle
Authors: Pu Zhe , Ren Bin , Tang Xiaoying , Wang Jifeng
Published: July 2020

Pressure vessel is an important part of industrial production. Pressure vessels usually have many nozzles, which are connected to other devices through pipeline. Due to the large thermal stress caused by the thermal expansion of the pipeline, the load on the nozzle of the connected vessel will be increased. When the load on the nozzle is too large, it may cause local deformation of the vessel, or even cause cracking at the root of the nozzle. Increasing the flexibility of the pipeline can reduce the load on the nozzle. Taking the flare system of the factory as an assessment case, this paper introduced a new load checking method. The software was used to simulate the load on the liquid separation tank connected with the flare gas pipeline. The calculated load of the liquid separation tank nozzle met the technical conditions of the manufacturer.
Precise Identification of Water Flooded Degree and Oil-water properties of Reservoir Based on Logging Interpretation
Authors: Wang Zhihui
Published: July 2020

The crude oil reserves are very rich in the peripheral tight oil-water layer. However, due to the lack of effective production technical means, reserves utilization is relatively low. Imbibition flooding is one of the critical technical measures for the efficient development of (weak) hydrophilic tight oil-water layer. To obtain high efficiency production technology for weak hydrophilic tight oil-water layer, we investigated the imbibition flooding effect of negative/non-ionic surfactant “HLX”, “SYH (petroleum sulfonate) +Na2CO3”, cationic surfactant “YANG” and non-ionic surfactant “DCY” on weak hydrophilic core with permeability of about 2.0 × 10−3 μm2. The study results suggest that the imbibition recovery rate and imbibition rate are affected not only by the interfacial tension of the oil-water layer but also by the rock pore wettability. The physical simulation experimental results indicate that the “YANG” and “DCY” imbibition can change the wettability of rock pore surface and reduce the interfacial tension. Hence, the imbibition flooding effect is relatively good, and the recovery rate is significantly increased.
A four kinetic model for delayed coking process of Qingdao vacuum residues
Authors: Li Na , Wang Yonggang , Zhao Dan
Published: July 2020

Batch coking reaction experiments of Qingdao vacuum residues were carried out in the temperature range of 420–480 °C and at reaction times in the range of 5–90 min. A four lump kinetic model was developed for delayed coking process of Qingdao vacuum residues. The feedstock and products were considered as a unique and three separated lumps, respectively, in the model. The product lumps were included gas (C1~C4), distillate (C5+~500 °C) and coke (toluene insoluble and 500+ °C). Reactions were assumed in first order and based on Arrhenius reaction rates. The kinetic model was developed to predict unconverted feed values and product yields. The results showed a very good agreement between the experimental yield and predicted yield of different pseudocuts was obtained.
Radial seepage characteristics of polymer solution in microfractured reservoir based on a fractal network model
Authors: Liu Guangwei , Yang Xipu , Guo Liwen , Zhang Xin , Liu Jun , Kang Botao
Published: July 2020

Accurate assessment of polymers’ flow behaviour is one of the key task for polymer flooding design in micro-fractured reservoir. In this paper, a fractal net model is developed for characterizing polymer flow in the micro-fractured reservoir based on straight capillary model, generalized Darcy’s law and constitutive equation for power-law fluids. A mathematical model for predicting the variation of pressure drop and effective permeability of polymer flow in porous media with network microstructure parameters and polymer power index is proposed. The developed model will help to calculate and characterize effective permeability alteration during polymer solutions seepage in micro-fractured media.
Research on Well-seismic Characterization of Multi-layer Sandstone Reservoir
Authors: Chen Changkui , Zhang Pan , Nian Bin , Huang Dongan
Published: July 2020

Multi-layer sandstone reservoirs are one of the important types of A dilute oil reservoirs. They have reached the middle and later stages of development, with the following characteristics: controlled by multiple multi-level faults, many faults, small fault blocks, small fault block reservoir area; affected by sedimentation, the distribution of sand bodies is discontinuous and the connectivity is poor, resulting in serious reservoir heterogeneity; after long-term water injection scouring, the reservoir properties and oil-water properties have changed, and the remaining oil distribution is complicated. These characteristics determine that the research focus of this type of reservoir is to carry out fine characterization of reservoir well-seismic joints, establish the isochronous stratigraphic framework of the reservoir unit, analyze the characteristics of small faults and microstructures in the reservoir, and describe various sand bodies between wells. The internal heterogeneity and the three-dimensional spatial distribution regularity of the oilfield are used to establish a fine three-dimensional reservoir geological model, which provides strong technical support for revealing the spatial distribution characteristics and laws of the remaining oil.
Reservoir classification and evaluation of Yan'an formation in Xifeng Oilfield
Authors: Sun Ning , Zhang Zhipeng , Li Zhenhua , Chen Zhanjun
Published: July 2020

According to reservoir lithology and the combination of pore throat, this paper takes porosity, permeability, pore throat diameter and displacement pressure as evaluation parameters to classify and evaluate the reservoir. Yan'an Formation reservoir in Xifeng Oilfield is divided into four types, I, II, III and IV, which correspond to four types of good, medium, poor and non reservoir respectively.From class I to class IV reservoir, the reservoir performance changes from good to bad, the porosity and permeability decrease, and the heterogeneity increases. The results of geological analysis show that the classification results are reasonable and have certain guiding significance for the exploration and development of oil and gas in the oilfield.
Application of Water Exchange Physical Model in Artificial New Port Town
Authors: Liu Guozhen , Zhang Qinfeng , Wang Yazheng , Liu Pei
Published: July 2020

The water exchange capacity of artificial river system in the new town formed by reclamation in the coastal water is studied by means of water exchange tidal physical model test. The model test results show that the water exchange capacity of Lake Wood area with good hydrodynamic condition is best and except for the top of the curve and the north port, the water exchange capacity of meandering canal is better, while that of south port is the weakest. Through comprehensive analysis, it is found that water exchange capability is mainly depend on the unidirectional flow velocity and duration. Taking prototype current data as reference, it indicates that long time unidirectional flow exists in the artificial river system which is conducive to the water exchange of the artificial river system. The results of typical tide water exchange test point out that the Lake Wood, north port and Strolling Canal can meet the requirement of fulfilling one exchanging per week, but the south port which is semi-closed and weakest in hydrodynamic can’t meet the water exchange requirement. So it is suggested that the south port should be modified to meet the requirement of water exchange.
Hiking to Well-being: Leisure Benefits for Personal and Social Development
Authors: Zhang Caihong
Published: July 2020

In recent years, hiking has developed rapidly, but research on the leisure benefits of hiking is still ignored. This research takes the Ancient Tea-Horse Road in Pu’er Yunnan Province as an example, and adopts a qualitative research method to conduct in-depth interviews with 21 interviewees. On this basis, the paper analyzes the motivation of the Ancient Tea-Horse Road hikers and reveals the main significance of hiking. The results show that the Ancient Tea-Horse Road hiking is a valuable option for an economical and enjoyable activity. High popularity, low-cost consumption and being able to meet the participants' experience demand are the key factors to attract the hikers. Two key themes related to leisure benefits emerged. Firstly, for the person, hiking can bring the participants relaxation, challenge oneself, identify cultural quality, enhance interpersonal feelings and develop social relations as well as other positive effects. Secondly, for the society, hiking can enrich tourism leisure products, inherit historical and cultural heritage, and improve the quality of tourism and leisure industry. Finally, the leisure benefits generation mechanism model of the Ancient Tea-Horse Road hiking and implications are discussed.
The reflection on architectural form caused by global issues such as population and ecology
Authors: Liu Yang
Published: July 2020

In 2011, Singapore held the Asian vertical city project design competition. Saudi Arabia is building the Jeddah tower, which is expected to be completed in 2020 and will be the world’s first skyscraper with a height of 1,000 meters. Jeddah tower perfectly embodies the concept of “vertical city”, which maximizes the living space and can accommodate the increasing urban population. The vertical scheme is an alternative to the horizontal land consumption, so the appearance of high-rise buildings significantly changes the urban environment.
Biodegradation of Fluoranthene Contaminated Soil by Different Combinations of Bacteria
Authors: Wang Mingzhe , Zhang Haonan , Li Guangchun
Published: July 2020

In this study, different combinations of three fluoranthene degrading bacteria YN420, YN1, E420 complex microorganisms were constructed through orthogonal experiment, and applied to the biodegradation of fluoranthene contaminated soil to determine the optimal combination of complex microorganism. The results showed that the degradation rate of fluoranthene in a soil slurry of different combinations of complex bacteria was higher than that of three strains inoculated alone. The optimal combination ratio of complex microorganism was YN420: YN1:E420=2:1:1, and different ratios of complex microorganism could be enhanced to the bioremediation of fluoranthene in contaminated soil.
Adsorption characteristics of Pb (II) onto red clay, bentonite and bone char
Authors: Li Gang , Zhang Jinli , Liu Jia
Published: July 2020

The adsorption characteristics of red clay, bentonite, bone char, modified red clay (97% red clay+3% bone char) and modified bentonite (97% bentonite+3% bone char) on Pb(II) were studied by batch test. Based on the experimental results, the Langmuir model and quasi second-order kinetic model were used to fit the experimental data. The results showed that the adsorption of Pb(II) by red clay, bentonite, and bone char is a rapid reaction process, and the adsorption capacity of bone char is significantly greater than that of red clay and bentonite. Langmuir model and quasi second-order kinetic model can be used to describe the isotherm adsorption and kinetic characteristics of red clay, bentonite and bone char, respectively. The adsorption capacity of the modified red clay or bentonite is significantly increased, and the adsorption capacity of the bentonite with 3% bone char is the best liner filler for Pb(II) pollutants.
Risk Evaluating of Chongqing Yangtze River Highway Tunnel Environment
Authors: Wang Yu , Zhao Yan , Li Yongyu , Ge Xiaoyan , Wang Shihua
Published: July 2020

The quantitative description on risk analysis is the assumption of risk management. Traditional risk assessment methods of engineering project are often affected by subjective factors. Fuzzy comprehensive evaluation by entropy weight model serve as a tool provide us a way to assess the risk. This new method could reduce or avoid the effect of subjective factors and fuzzy factors. This article introduce the basic theory of the method and analyze the risk of Chongqing Yangtze River Highway Tunnel environment, then calculates various risks factor using the entropy power the weight, and combines fuzzy mathematics method to establish evaluation model by combining qualitative analysis and quantificational computability, to evaluate the risk factor and to draw the conclusion. The practical analysis has proven that this method is preferable and feasible.
Analysis and Optimization of Garbage Removal System in Jiamusi City
Authors: Jia Xiaoqian , Sun Yanbin , Wen Bin , Zhang Yuehua , Guan Jinqiu , Li Lan
Published: July 2020

With the development of the social environment, the amount of urban domestic garbage has increased rapidly, and garbage removal has become particularly important, which severely affects social-environmental resources. At present, the level of waste disposal Jiamusi City, far behind the rate of discharge of garbage, removal of garbage, and recycling efficiency is not high. To reduce environmental damage and waste of resources, it is necessary to improve the efficiency of waste removal and recycling. This paper analyses the current situation of the garbage removal and transportation system in Jiamusi City, establishes a mathematical model to solve it in mat lab, and uses genetic algorithm and particle swarm optimization to obtain the optimal path for garbage transportation. Combined with example verification, the results of the two algorithms are obtained and compared respectively, and an algorithm suitable for optimizing the waste removal path is derived.
Uptake of uranyl (UO2
2+) in water body by sago pondweed
Authors: Yi Zhengji , Liu Jian , Liu Xing , Zeng Rongying , Cui Ying
Published: July 2020

Uranium pollution is posing severe threat to the human environment. In the current research, we studied the applicability of Stuckenia pectinata (sago pondweed) powder as a new sort of biosorbent for uranyl removal from effluent. A series of batch experiments were conducted to explore impact of shaking time, solution pH, and initial U(VI) level upon U(VI) biosorption onto Stuckenia pectinata powder. The results show that the biosorption process is highly dependent upon pH value in the range of 3.0-6.5. The pH value of 5.5 is preferable to uranium elimination. The U(VI) biosorption equilibrium can be achieved after 60 min. The Stuckenia pectinata has a maximum uranium biosorption capacity of 268.82 mg·g−1. In brief, the obtained results suggest that Stuckenia pectinata may be utilized as a promising biosorbent for efficient removal of U(VI) from effluent.
The Effect of Environmental Engineering on Existing Venues and Operation Management: A Case Study of Minxiong Township
Authors: Liang Chou-fu , Li Xin-yu , Lin Tzu-Yun , Lin Hsiao-Hsien
Published: July 2020

This study investigated the effect of environmental engineering on existing venues and fields and operation management. By using a literature review, questionnaire, and qualitative methods, we interviewed 9 residents and collected 420 questionnaires. Subsequently, the collected data was analyzed using multiple examinations and discussed. Environmental engineering can promote economic, social, and environmental development. However, a lack of consensus regarding numerous challenges among decision makers and businesses can reduce the number of visitors and affect the efficiency of facility management. Challenges include reducing dust emissions, revising fence planning, adjusting transportation lines, improving site survey accuracy, and reducing construction errors. These problems can affect visitor numbers and operation management even if businesses are effective in operation, marketing, and management and maintain professional teaching and service quality.