Commercial Software Tools Research Articles

Eco-Design and its Tools - Attempted use in the Military Industry

Abstract The development of military technology in recent years has made tremendous progress. However, some of these technologies have a direct impact on environmental degradation. This makes it necessary to introduce new solutions and technologies in the field of environmental protection. The paper provides a literature review on issues such as eco-design and its tools, life cycle assessment as well as attempted use of them in the defence sector. The environmental regulations and standards ensuring the quality of defence product have been described. In the military industry whose priorities are primarily related to defense the classic approach to design and its tools focused its attention on safety, functionality, ergonomics, costs, strength and technical parameters, instead of environmental problems. In fact militarism has huge impact on the climate because of giant greenhouse gas emissions, the main problem of the Armed Forces is the increased carbon footprint emissions which should be reduce of therefore case studies of eco-design and its tools, commercial software tools for carbon footprint calculation and life cycle assessment are described. The research is co-financed under the Program of the Ministry of Science and Higher Education “Implementation Doctorate”.

Parabolic trough solar collectors: A general overview of technology, industrial applications, energy market, modeling, and standards

AbstractMany innovative technologies have been developed around the world to meet its energy demands using renewable and nonrenewable resources. Solar energy is one of the most important emerging renewable energy resources in recent times. This study aims to present the state-of-the-art of parabolic trough solar collector technology with a focus on different thermal performance analysis methods and components used in the fabrication of collector together with different construction materials and their properties. Further, its industrial applications (such as heating, cooling, or concentrating photovoltaics), solar energy conversion processes, and technological advancements in these areas are discussed. Guidelines on commercial software tools used for performance analysis of parabolic trough collectors, and international standards related to performance analysis, quality of materials, and durability of parabolic trough collectors are compiled. Finally, a market overview is presented to show the importance and feasibility of this technology. We believe the compilation of reviews related to the above aspects will further provide impetus for the development of this technology in the near future.

RETRACTED: Numerical and experimental cavitation assessment of near-wake characteristics of hydrodynamic performance characteristics of cavitating flow with and without ultrasonic transducers

Abstract The primary objective of this research is to study the cavitating effects of fluid flow past a cylinder. Experimental and numerical investigation is carried out to study the effect of cylinder diameter and its length on the formation of wake cavitation in the upper sub-critical flow regime, which corresponds to Reynolds number (Re) in the range of 2 × 104 to 2 × 105. Additionally, to enhance the cavitation phenomena, an ultrasonic transducer is designed. The commercial software tool, ANSYS Fluent 17.2, is used to simplify three dimensional Reynolds averaged Navier Stokes equation with the compressible fluid flow by considering the pressure-based solver with standard K- ω turbulence model. The Schnerr and Sauer cavitation model is employed to study the cavitation phenomena. Results reported that with an increase in the cavitation number, the size of the wake cavity decreased. Also, the size and the length of the wake cavity depend on the diameter of the cylinder and the size of the step provided. A comparison of the numerical and experimental results shows that the numerical method is able to predict accurately the shape parameters of the natural cavitation phenomena such as cavity length, cavity diameter and cavity shape. The results also indicate the drag coefficient decreases up to 40% when the stepped cylinder size in reduction is observed, provided Reynolds number remains constant. Also, for the plain cylinder the drag coefficient rises by 28% when cavitation number is increased from 0.25 to 0.32.

Comparative analysis of monofacial and bifacial photovoltaic modules for floating power plants

The aim of this study is to create usable commercial simulation software tools for photovoltaic (PV) systems even in the case of floating applications. Using the experimental data of a plant installed at the “Enel Innovation Lab” in Catania (IT), adequate heat exchange coefficients of the software's thermal models were found, which allowed us to take into account the thermal effects for these types of installations. An optimization of the sizes for mono- and bifacial floating systems was carried out. The simulated data for a ground system were compared with the floating data through performance indices. In addition, monofacial models were compared with bifacial. The optimized variables are the tilt angle and the pitch, whereas for the bifacial systems, the module elevation is also considered. The albedo is a sensitive factor mainly for the bifacial modules, so it was considered a parameter in the different design solutions. The simulations were performed by two specialized commercial software programs, where different PV system models are implemented. The normalized annual energy yield was chosen as a meaningful parameter with which to compare the different solutions. As the analysis of PV systems is highly site dependent, the study was developed for two locations, characterized by different diffuse and albedo solar irradiance components, specifically at high latitudes (Frankfurt, DE) and at intermediate latitudes (Catania, IT).

Automatic detection of the best performing priority rule for the resource-constrained project scheduling problem

Priority rules are applied in many commercial software tools for scheduling projects under limited resources because of their known advantages such as the ease of implementation, their intuitive working, and their fast speed. Moreover, while numerous research papers present comparison studies between different priority rules, managers often do not know which rules should be used for their specific project, and therefore have no other choice than selecting a priority rule at random and hope for the best.This paper introduces a decision tree approach to classify and detect the best performing priority rule for the resource-constrained project scheduling problem (RCPSP). The research relies on two classification models to map project indicators onto the performance of the priority rule. Using such models, the performance of each priority rule can be predicted, and these predictions are then used to automatically select the best performing priority rule for a specific project with known network and resource indicator values.A set of computational experiment is set up to evaluate the performance of the newly proposed classification models using the most well-known priority rules from the literature. The experiments compare the performance of multi-label classification models with multi-class classification models, and show that these models can outperform the average performance of using any single priority rule. It will be argued that this approach can be easily extended to any extension of the RCPSP without changing the methodology used in this study.

Analysis of Sand-Control-Installation Failures Provides Insights, Paths Forward

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 199251, “Understanding Sand-Control-Installation Failures,” by Raymond Tibbles, SPE, Kesavan Govinathan, SPE, and Ian Mickelburgh, SPE, DuneFront, et al., prepared for the 2020 SPE International Conference and Exhibition on Formation Damage Control, 19-21 February, Lafayette, Louisiana. The paper has not been peer reviewed. Sand-control-installation failures range from minor issues that can be remedied easily to catastrophic events that put the entire well and investment at risk. The complete paper introduces several case studies of such failures and details the investigative process and techniques used to identify root causes. A commercial software tool incorporating data-analysis techniques and a methodical evaluation work flow were used to understand the cause of the failures and determine how they can be prevented in future operations. Examples include events such as screen and washpipe damage, bridging, hole collapse, and packer-seal failure. Introduction Potential modes of failure tradition ally have been investigated with material- balance calculations and surface-pressure measurements. However, this simple approach is unable to diagnose clearly the specific failure mode and often is insufficiently precise to be conclusive, especially for high-value wells. While surface data provide an overview of the operation, the data are influenced by many factors involving the entire system, making it difficult to differentiate multiple events and locate them in the flow path. Mass-balance calculation is also a rudimentary analysis with many inherent assumptions. Often, estimations of perforation or openhole volumes are inaccurate, location of voids cannot be identified in the event of an incomplete pack, and gravel volume and mass measurements do not help in understanding packing mechanisms. Attempts have been made to develop logging techniques to obtain a clearer picture of the outcome of a gravel pack. While this effort has met with some success in cased holes, it has proved to be difficult to apply in open holes. Regardless, identification of the presence of voids in a gravel pack does not provide a clear explanation of why they formed and how they may be prevented in the future.

Aerodynamic investigation of the shock train in a scramjet with the effects of backpressure and divergent angles

AbstractNumerical simulations are carried out to study the effect of divergence angle and adverse pressure gradient on the movement of a shock wave train in a scramjet isolator. The commercial software tool ANSYS Fluent 16 was used to simplify the two‐dimensional Reynolds‐averaged Navier‐Stokes equation with the compressible fluid flow by considering the density‐based solver with the standard k‐ε turbulence model. The species transport model with a single‐step volumetric reaction mechanism is employed. Initially, the simulated results are validated with experimental results available in the open literature. The obtained results show that the variation of the divergence angle and backpressure on the scramjet isolator has greater significance on the flow field. Also, with an increase in the backpressure, due to the intense turbulent combustion, the shock wave train developed should expand along the length and also move towards the leading edge of the isolator leading to a rapid rise in the pressure so that the pressure at the entrance of the isolator can match the enhanced backpressures.

Starting point selection approach for power system model validation using event playback

Model validation is an essential task to determine whether a model can accurately describe the actual behaviours of a power system. Currently, major commercial software tools are equipped with an ‘event playback’ function to validate dynamic models using testing data from phasor measurement units (PMUs). Due to their limited bandwidth and low sampling rates, PMUs cannot capture the fast-transient dynamics. As such, the playback function using the conventional approach may mistakenly invalidate an accurate model during the high-frequency responses. To overcome the deficiency, a batch state estimation approach is proposed in this study to improve the performance of the ‘event playback’ function by focusing on low-frequency responses in model validation. The proposed approach consists of three major steps. First, a multi-model adaptive Kalman filter approach is used to estimate the dynamic states of the system. Second, the singular spectrum analysis (SSA) is used to detect the fault clearance time. Finally, the estimated states after the fault are used as the initial states of the ‘event playback’ to validate the dynamic model during the low-frequency responses. The analytical basis of the proposed method is also provided by showing the existence and uniqueness of the trajectory of the underlying model. The effectiveness of the proposed approach is demonstrated using the PSS/E.

Computational modeling on supercavitating flow over axisymmetric cavitators

Numerical simulations are carried out to analyse the cavitating effects over the circular disk cavitator and cone cavitator. The commercial software tool ANSYS Fluent 16 was used to simplify two dimensional Reynolds averaged Navier Stokes equation with the compressible fluid flow by considering the pressure-based solver with standard K- ω turbulence model. The Schnerr and Sauer cavitation model is employed to study the cavitation phenomena. The simulations are done by varying the diameter of circular disk and cone cavitator, by varying fixed cavitation numbers and by varying flow pressures. Initially flow past circular cavitator will be analysed by varying the cavity length and validated with other existing models [i.e., Kunz cavitation and full cavitation model]. Simultaneously, to analyse the capability and robustness of the computational analysis cone cavitator are adopted. The obtained results from the simulation are then validated with the experimental and theoretical correlations.

A rapid analysis platform for investigating the cellular locations of bacteria using two-photon fluorescence lifetime imaging microscopy

Facultative intracellular pathogens are able to live inside and outside host cells. It is highly desirable to differentiate their cellular locations for the purposes of fundamental research and clinical applications. In this work, we developed a novel analysis platform that allows users to choose two analysis models: amplitude weighted lifetime (τA) and intensity weighted lifetime (τI) for fluorescence lifetime imaging microscopy (FLIM). We applied these two models to analyse FLIM images of mouse Raw macrophage cells that were infected with bacteria Shigella Sonnei, adherent and invasive E. coli (AIEC) and Lactobacillus. The results show that the fluorescence lifetimes of bacteria depend on their cellular locations. The τA model is superior in visually differentiating bacteria that are in extra- and intra-cellular and membrane-bounded locations, whereas the τI model show excellent precision. Both models show speedy performances that analysis can be performed within 0.3 s. We also compared the proposed models with a widely used commercial software tool (τC, SPC Image, Becker & Hickl GmbH), showing similar τI and τC results. The platform also allows users to perform phasor analysis with great flexibility to pinpoint the regions of interest from lifetime images as well as phasor plots. This platform holds the disruptive potential of replacing z-stack imaging for identifying intracellular bacteria.

Inter- and intra-software reproducibility of computed tomography lung density measurements.

Multiple commercial, open-source, and academic software tools exist for objective quantification of lung density in computed tomography (CT) images. The purpose of this study was to evaluate the intersoftware reproducibility of CT lung density measurements. Computed tomography images from 50 participants from the COPDGeneTM cohort study were randomly selected for analysis; n=10 participants across each global initiative for chronic obstructive lung disease (GOLD) grade (GOLD 0-IV). Academic-based groups (n=4) and commercial vendors (n=4) participated anonymously to generate CT lung density measurements using their software tools. Computed tomography total lung volume (TLV), percentage of the low attenuation areas in the lung with Hounsfield unit (HU) values below -950HU (LAA950 ), and the HU value corresponding to the 15th percentile on the parenchymal density histogram (Perc15) were included in the analysis. The intersoftware bias and reproducibility coefficient (RDC) was generated with and without quality assurance (QA) for manual correction of the lung segmentation; intrasoftware bias and RDC was also generated by repeated measurements on the same images. Intersoftware mean bias was within ±0.22mL, ±0.46%, and ±0.97HU for TLV, LAA950 and Perc15, respectively. The RDC was 0.35L, 1.2% and 1.8HU for TLV, LAA950 and Perc15, respectively. Intersoftware RDC remained unchanged following QA: 0.35L, 1.2% and 1.8HU for TLV, LAA950 and Perc15, respectively. All software investigated had an intrasoftware RDC of 0. The RDC was comparable for TLV, LAA950 and Perc15 measurements, respectively, for academic-based groups/commercial vendor-based software tools: 0.39L/0.32L, 1.2%/1.2%, and 1.7HU/1.6HU. Multivariable regression analysis showed that academic-based software tools had greater within-subject standard deviation of TLV than commercial vendors, but no significant differences between academic and commercial groups were found for LAA950 or Perc15 measurements. Computed tomography total lung volume and lung density measurement bias and reproducibility was reported across eight different software tools. Bias was negligible across vendors, reproducibility was comparable for software tools generated by academic-based groups and commercial vendors, and segmentation QA had negligible impact on measurement variability between software tools. In summary, results from this study report the amount of additional measurement variability that should be accounted for when using different software tools to measure lung density longitudinally with well-standardized image acquisition protocols. However, intrasoftware reproducibility was deterministic for all cases so use of the same software tool to reduce variability for serial studies is highly recommended.

Prediction and optimization of indoor thermal environment and energy consumption based on artificial neural network

Commercial software and simulation tools frequently used by researchers in predicting indoor thermal condition and energy consumption of a green building can ensure high precision, however, the computational process are usually time-consuming and cannot clearly and directly give suggestions for a ‘greener’ design. This paper aimed to develop a novel model based on artificial neural network (ANN) to speed up the simulation and provide optimal design solutions. Training and testing data representing design scenarios of different insulation thickness, shading coefficient, ventilation rate and their corresponding Annual Energy Demand (AED) and Uncomfortable Degree Hours (UDH) value were obtained from a numerical analysis model at first. The deduced ANN model was tested and validated, showing very high accuracy as a predictor for broad range of inputs. Relationship between design parameters and outputs were analysed and presented intuitively. The ANN results directly offered suggestions of minimizing AED and UDH, the optimum solution was to reduce ventilation and increase insulation to the limit, and reduce shading coefficient form base-case 0.5 to approximately 0.2. UDH could be lessened by 4% and AED could be reduced by nearly 29% compared to the base case design in this way.

A survey on gel images analysis software tools

One of the most severe sources of information for a molecular biologist is the gel image generated by using gel electrophoresis during the experiment of issr-pcr, sds-pages, and rapd-pcr. DNA and protein gel images are obtained through the gel electrophoresis separations techniques of DNA and protein fragments. The separation of the polymorphic bands is based on the sizes of the negatively charged DNA fragments running from the negative cathode toward the positive anode. Each gel image has some vertical lanes; each lane corresponds to one sample and has several horizontal bands. The resulting images produced by Gel electrophoresis are sometimes difficult to interpret so that it was important to develop software tools to analyze the gel images to help biologists in the process of analyzing gel image as they draw their conclusions according to the results that generated from gel image analyzer software. In this article, we present a survey of some commercial and non-commercial software tools that are used for analyzing gel images. We develop a novel software for processing and analyzing the gel electrophoresis images, computing the molecular weights, saving them as excel sheet, clustering the bands based on their molecular weights using k-means algorithm, Applying band matching using a tolerance value entered by the user, determine the similarities between samples, drawing the corresponding phylogenetic tree, saving a report of the experiment as a pdf, and printing this report. The novel software will provide the biologist with the ability of manual processing, automatic processing, and semi-automatic processing.

Understanding the requirements Of the Indian IT industry using web scrapping

Abstract India produces over two million engineering graduates a year as well as another million graduates in related fields such as computer science, biotechnology etc. Employers cite new graduates lack communication skills, problem solving skills and technical skills. The Indian Information Technology (IT) sector has fast changing technical requirements and understanding its requirement is very important for academics and professional trainers so that they can better prepare students with relevant skills. In this paper, we have developed a simple methodology to analyse the requirements of the Indian IT industry by parsing their job portals and extracting information from their job descriptions. We selected the top 10 IT companies by market cap to conduct our analysis. We extracted the number of jobs that contained each keywords like Java, CCNA, SAP, Agile and computed the popularity of each skill and ranked them accordingly. We find that IT industry requires software and skills like Java, Python, SQL are covered by most universities but paid and in demand commercial software tools like SAP, Oracle are not part of the curriculum. This methodology can also track the evolution of skills and predict new skills that can become popular in Industries in the future.

Bio-inspired generative design for support structure generation and optimization in Additive Manufacturing (AM)

Additive Manufacturing (AM) is widely used to manufacture complex and personalized medical components. However, the generation and manually removing of support structures in the pre- and post-processing stages are still time-consuming and costly. To improve the automation of preparation while reducing support structure volume, post-processing time and cost, this paper proposes a bio-inspired generative design method, integrating parametric L systems, evolutionary optimization and an AM processing simulation model, to generate light-weight, easy-to-remove and heat-diffusion-friendly biomimetic support structures. Dental components are modelled and manufactured for validating the proposed method. The results obtained are compared with that of existing commercial software tools.

On the analysis of capacitive rectangular waveguide discontinuities close to arbitrarily shaped conducting and dielectric posts

In this work, we propose an integral equation technique for the efficient analysis of capacitive step discontinuities in rectangular waveguides. The method allows for the inclusion of a number of arbitrarily shaped posts in the vicinity of the step discontinuity. The posts can be both metallic or composed of homogeneous dielectric materials. The integral equation formulation is based on the Surface Equivalence Principle, and uses the parallel plate Green’s functions that take into account for the boundary conditions imposed by the host waveguide. The formulation is written in the mixed spatial-spectral frequency domain, and takes advantage of the symmetry of the problem by reducing the original three dimensional (3D) problem to a so called 2.5D problem. The numerical technique has been validated with simulation examples, namely, two lowpass filters that use conducting and dielectric posts of different shapes as impedance inverters. The results provided by the method that we propose have been also compared to those obtained with a commercial full-wave software tool (ANSYS HFSS), showing in all cases a very good agreement with substantially higher computational efficiency.

High‐order shape functions for interior acoustics

AbstractThe acoustic behavior of structures has lately been in the focus of industrial applications, due to the fact that the acoustic emission of a product is one major parameter which significantly influences the customer perception with respect to comfort and functionality. In this context, the numerical simulation of vibroacoustic problems needs to provide reliable information in order to be able to evaluate the acoustic behavior of new products already in an early stage of the product development cycle. With the help of a suitable simulation model expensive experimental studies can be reduced and acoustically improved designs can be developed. However, there are already commercial software tools available which offer the opportunity to solve coupled vibroacoustic problems. These tools are typically based on conventional low‐order finite element methods (h‐FEM) for solving the governing partial differential equations (PDEs) of the problem. In this contribution, the advantages of high‐order finite element methods, such as a possibly exponential rates of convergence, will be exploited. Based on this approach a similar accuracy compared to classical h‐FEM simulations using significantly less degrees of freedom (dof) can be achieved. Consequently, the computational time required for the analysis can be notably reduced for a given error threshold. Reducing the computational effort is of special importance when investigating complex structures of practical relevance. Even today, the overall efficiency of the simulation process is still an issue, despite the ever growing computational power. To exploit the described advantages, high‐order FEMs have to be extended to acoustical problems. In this contribution the developed high‐order simulation approach is discussed and the obtained results are compared to commercial finite element solutions focussing on the accuracy and the computational effort of the different approaches.

Predicting Naphthenic Acid Migration Through the Foundation of Oil Sands Tailing Pond

In this paper, a conceptual model was developed to predict the seepage of oil sands process-affected water with capabilities of evaluating the transport and attenuation of naphthenic acids through the dykes and the foundations of oil sands tailings pond. The model incorporates naphthenic acid diffusion, adsorption, dispersion, advection, and biodegradation, and was modeled through the commercial software tools to predict naphthenic acid fate in both spatial and time scales. The tailing pond of the Muskeg River Mine in the Athabasca oil sands deposit was investigated in the case study. The comparison between the onsite monitoring data and the simulation results was in good agreement. In addition, limiting factors for migration of naphthenic acid were also discussed based on a parametric sensitivity study.

3D DIGITAL RECONSTRUCTION BASED ON ARCHIVED TERRESTRIAL PHOTOGRAPHS FROM METRIC CAMERAS

The paper deals with the possibilities and limitations of the image processing of digitalized terrestrial photographs from analogue metric cameras. By the end of the 20th century, analogue metric cameras such as Zeiss UMK were used for documentation purposes in the fields of industrial and investment construction, nature and landscape preservation, heritage preservation, etc. Currently, the collections of photographs are stored at specialized archives of many different institutions, such as libraries, museums, universities, etc. These sets of photographs provide a material background for a 3D digital reconstruction of a subject of interest at the time of taking the photographs. The digital image processing of old photographs may be more difficult due to unknown parameters of the used camera, such as the focal length, image coordinates of the fiducial marks and distortion parameters of the lens system, etc. In this case, it may be difficult to process these photographs in a photogrammetric software. The paper presents a methodology for the digital photogrammetric processing of analogue terrestrial photographs. The data processing is based on the parameters of the used metric cameras, which are described in their calibration reports. The image processing was tested in two commercial photogrammetric software tools that utilize the technology of Structure-from-Motion (SfM) or multiimage intersection photogrammetry to process image datasets.

Optimization of seismic response of steel structure using negative stiffness damper

Earthquakes of greater magnitude can cause stark destruction. Seismic protection of structures is one important tool to minimize damages and total collapse of structures. Researchers have made many attempts to achieve this goal with various techniques and one such strategy of seismic response control developed is introducing true negative stiffness in the structure. True negative stiffness is introduced with the help of negative stiffness damper (NSD). The NSD generates force in the direction of the displacement and hence it is called negative stiffness. The present study focuses on modelling NSD device in a commercial software tool (ETABS 2016). Further the device is implemented on 2D steel frame models and seismic parameters such as base shear, storey displacement and top storey acceleration are studied.