Standard Design Parameters Research Articles

Dynamic Occlusion Modeling and Clearance Control of the Visual Field of Curved Highway Roadside Landscape

In order to solve the control of the degree of anti-occlusion of the roadside landscape of the expressway curve according to the drivers’ visual characteristics during high-speed driving, a dynamic space model of the visual process of curved highway roadside landscape was established, and the calculation equation of roadside landscape visual field was derived. The dynamic occlusion ratio was defined by space coordinates, and the judgment model was proposed for the de-occlusion of the roadside landscape visual field. According to the standard design parameters of the G4 Highway Hunan section, the occlusion laws were analyzed by MATLAB for different widths and different heights of obstructions as well as the same widths and heights of obstructions at different positions in the roadside landscape visual field, thus the control value and control content of anti-occlusion clearance for the roadside landscapes were proposed. The results show that the anti-occlusion clearance control range of the roadside landscape is 270 m at the design speed of 120 km/h, 220 m at 100 km/h, and 170 m at 80 km/h. The control value of clearance width is 25 m, and the control value of clearance height is recommended to be 20 m. Within the scope of highway land expropriation, it is recommended to land expropriation 25 m wide from the road boundary. The research provides model support for building the closeness and openness of highway roadside landscape.

Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections.

The rise in antimicrobial resistance (AMR), and increase in treatment-refractory AMR infections, generates an urgent need to accelerate the discovery and development of novel anti-infectives. Preclinical animal models play a crucial role in assessing the efficacy of novel drugs, informing human dosing regimens and progressing drug candidates into the clinic. The Innovative Medicines Initiative-funded “Collaboration for prevention and treatment of MDR bacterial infections” (COMBINE) consortium is establishing a validated and globally harmonized preclinical model to increase reproducibility and more reliably translate results from animals to humans. Toward this goal, in April 2021, COMBINE organized the expert workshop “Advancing toward a standardized murine model to evaluate treatments for AMR lung infections”. This workshop explored the conduct and interpretation of mouse infection models, with presentations on PK/PD and efficacy studies of small molecule antibiotics, combination treatments (β-lactam/β-lactamase inhibitor), bacteriophage therapy, monoclonal antibodies and iron sequestering molecules, with a focus on the major Gram-negative AMR respiratory pathogens Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii. Here we summarize the factors of variability that we identified in murine lung infection models used for antimicrobial efficacy testing, as well as the workshop presentations, panel discussions and the survey results for the harmonization of key experimental parameters. The resulting recommendations for standard design parameters are presented in this document and will provide the basis for the development of a harmonized and bench-marked efficacy studies in preclinical murine pneumonia model.

A Digitalized Design Risk Analysis Tool with Machine-Learning Algorithm for EPC Contractor’s Technical Specifications Assessment on Bidding

Engineering, Procurement, and Construction (EPC) projects span the entire cycle of industrial plants, from bidding to engineering, construction, and start-up operation and maintenance. Most EPC contractors do not have systematic decision-making tools when bidding for the project; therefore, they rely on manual analysis and experience in evaluating the bidding contract documents, including technical specifications. Oftentimes, they miss or underestimate the presence of technical risk clauses or risk severity, potentially create with a low bid price and tight construction schedule, and eventually experience severe cost overrun or/and completion delays. Through this study, two digital modules, Technical Risk Extraction and Design Parameter Extraction, were developed to extract and analyze risks in the project’s technical specifications based on machine learning and AI algorithms. In the Technical Risk Extraction module, technical risk keywords in the bidding technical specifications are collected, lexiconized, and then extracted through phrase matcher technology, a machine learning natural language processing technique. The Design Parameter Extraction module compares the collected engineering standards’ so-called standard design parameters and the plant owner’s technical requirements on the bid so that a contractor’s engineers can detect the difference between them and negotiate them. As described above, through the two modules, the risk clauses of the technical specifications of the project are extracted, and the risks are detected and reconsidered in the bidding or execution of the project, thereby minimizing project risk and providing a theoretical foundation and system for contractors. As a result of the pilot test performed to verify the performance and validity of the two modules, the design risk extraction accuracy of the system module has a relative advantage of 50 percent or more, compared to the risk extraction accuracy of manual evaluation by engineers. In addition, the speed of the automatic extraction and analysis of the system modules are 80 times faster than the engineer’s manual analysis time, thereby minimizing project loss due to errors or omissions due to design risk analysis during the project bidding period with a set deadline.

Modification and Optimization of Groundnut (Arachis hypogaea) Roasting Machine

Roasting of groundnut is essential to ensure quality improvement, easy handling, safe storage, further processing, and value addition of the product. Therefore, the aim of the study was modified and optimized a groundnut roasting machine. Standard design parameters were used for the design modification. The design of the experiment had 27 runs. Machine speed (6.60, 12.80 and 19 rpm), roasting temperature (120, 160 and 200℃), and feed rate (120, 180 and 240 kg/h) were used as independent parameters, and the response variables include the moisture content of the groundnut, roasting efficiency, mechanical damage, throughput and quality efficiency of the machine. Response Surface Methodology (RSM) of the Design Expert Version 11 was adopted for the optimization process by applying the central composite design method for the Analysis of Variance (ANOVA) and optimized responses within the limit of the independent factors tested. Roasting temperature (200℃), machine speed (19 rpm) and feed rate (240 kg/h) were found as the optimum operational conditions which will optimally result in the optimal machine performance of 8.76% moisture content (r2 = 0.94), 76.99% roasting efficiency (r2 = 0.90), 2.46% mechanical damage (r2 = 0.86), 62.32 kg/h machine throughput (r2 = 0.98), 74.3% quality performance efficiency (r2 = 0.86) with the high desirability of 88%. An increase in machine speed increased the moisture content of the groundnut, roasting efficiency, mechanical damage, throughput, and quality efficiency of the machine. The study showed the optimal machine parameters for a groundnut roasting machine.

Baffling efficiency insights gained from tracer studies at 32 Washington treatment plants

This article summarizes tracer studies performed at 32 water treatment plants in Washington State ranging from 5 to 5,400 gpm, with contact basins from 200 gal to 1.5 mil gal. Multiple tracer studies were performed at each plant. The goal of the tracer studies was to determine the baffling efficiency (BE) of each basin by determining T10/T, where T10 is the time at which 10% of a tracer is measured at the outlet of a basin, and T is the hydraulic residence time. The tracer studies indicated that most facilities historically used BE values higher than what the tracer studies indicated for calculating compliance with disinfection regulations. The majority of the basins were rectangular, baffled basins. The tracer studies indicated that standard design parameters, such as length‐to‐width ratio, were not as accurate in predicting basin performance compared with calculating baffled channel cross‐sectional velocity. This effect was pronounced where cross‐sectional flow velocity was below the Reynolds laminar flow threshold. For circular, baffled basins, a relationship between cross‐sectional velocity and BE was also evident. The study also identified issues with plants having parallel, chlorine contact basins where uneven flow splitting between basins created an overall system BE less than the BE of individual basins.

Performance Comparison of Belleville Washer under Compressive Load using Experimental and Simulation Methods

Belleville washers are used in the different engineering applications with standard design parameters. The present work shows the behavior of stress and deflection of the standard Belleville washer compared to the non-standard design parameter as per the industrial needs. Belleville washer (or) disk spring with higher height to thickness ratio i.e. (h/t) is made with a bearing flat at upper Inner Diameter (I.D) and lower Outer Diameter (I.D) with appropriate radius over edge. The Belleville washer design parameter is analyzed by numerical, experimental and LS-Dyna FEM simulation. FEM simulations were performed by using commercial simulation software LS-Dyna to study the behaviors of stress and deflection of the standard and non-standard Belleville washer. During the study it was observed that variation between simulation and experimental results. The difference was reduced by using element formation criterion available in LS-Dyna. Finally the simulation and experiment results were matched by using particular element formation of 8 node hexagonal elements.

Experimental study on the performance evaluation and emission reduction potential of different cookstove models using standard design parameters and testing protocols

ABSTRACTThis article presents the design, development, experimental evaluation and parametric study of different biomass cookstove models using different feedstock having typical characteristics. This study is based on the emission reduction potential, energy, exergy, and power output by varying the quantity of different fuel wood while following the water boiling test protocols. Although the results obtained in this article exhibits several trends, with different types and quantity of wood yet are found to be consistent and comparable with one another. However, some trends are found to be very interesting and different from those already available in the literature. These results also exhibit that a specific model performs better than others in one condition, while the other does so for other set of operating conditions. This study presented here also explores the possibility for new scientific insights in the design, development and dissemination of improved biomass cookstoves in the field of sustainable development of society.

Experimental investigation of varying the fuel injection pressure in a direct injection diesel engine fuelled with methyl ester of neem oil

ABSTRACTBeing a fuel of different origin, the standard design parameters of a diesel engine may not be suitable for methyl ester of neem oil (MENO). So the engine parameters need to be optimised to suit the specific fuel properties. This experimental investigation is to find the effects of one of the engine parameters, that is, fuel injection pressure (FIP) jointly on the performance with regard to brake thermal efficiency (BTE), brake-specific energy consumption (BSEC), and emissions of carbon monoxide, carbon dioxide, hydrocarbon, nitrogen oxides, and smoke intensity with neat MENO as fuel. Comparison of performance and emission test were done for different values of IP to find the best possible IP for the optimum performance and emission. The optimum FIP was found to be 240 bar. It is found that the increase in IP increases the BTE and reduces the BSEC while having lower emissions.

Effect of Compression Ratio on Emission of CI Engine using Neat Karanja Oil and Karanja Oil Methyl Ester Blends

The standard design parameters of a compression ignition engine fail to give specified performance with strait vegetable oil (SVO) from different origins. This study is performed to find the effect of compression ratio on emission characteristics such as carbon monoxide (CO), carbon dioxide (CO2), hydrocarbon (HC), nitrogen oxides (NOx) and smoke opacity with all the tested fuels in a single cylinder, four stroke VCR engine fueled with neat Karanja oil blends (10 and 20%) with diesel (on volume basis) and Karanja oil methyl ester (KOME) blends (20, 40 and 60%) and compare the results with diesel. Experiments haves been conducted at compression ratios of 16:1, 17:1, 18:1. At higher CR, minimum value of CO is recorded as being 0.04 for 20% blend of KOME (B20), while maximum CO2 is4.45%. Lowest HC and NOx emission recorded are 22 ppm and 552 ppm respectively for 40% blend of KOME (B40). Emissions are marginally higher for K10 and K20 than for diesel. Overall observation shows that B40 has the lowest emissions among other blends of KOME at higher compression ratios.

Link Protein N-terminal Peptide Binds to Bone Morphogenetic Protein (BMP) Type II Receptor and Drives Matrix Protein Expression in Rabbit Intervertebral Disc Cells

Intervertebral disc (IVD) degeneration and associated spinal disorders are leading sources of morbidity, and they can be responsible for chronic low back pain. Treatments for degenerative disc diseases continue to be a challenge. Intensive research is now focusing on promoting regeneration of degenerated discs by stimulating production of the disc matrix. Link protein N-terminal peptide (LPP) is a proteolytic fragment of link protein, an important cross-linker and stabilizer of the major structural components of cartilage, aggrecan and hyaluronan. In this study we investigated LPP action in rabbit primary intervertebral disc cells cultured ex vivo in a three-dimensional alginate matrix. Our data reveal that LPP promotes disc matrix production, which was evidenced by increased expression of the chondrocyte-specific transcription factor SOX9 and the extracellular matrix macromolecules aggrecan and collagen II. Using colocalization and pulldown studies we further document a noggin-insensitive direct peptide-protein association between LPP and BMP-RII. This association mediated Smad signaling that converges on BMP genes leading to expression of BMP-4 and BMP-7. Furthermore, through a cell-autonomous loop BMP-4 and BMP-7 intensified Smad1/5 signaling though a feedforward circuit involving BMP-RI, ultimately promoting expression of SOX9 and downstream aggrecan and collagen II genes. Our data define a complex regulatory signaling cascade initiated by LPP and suggest that LPP may be a useful therapeutic substitute for direct BMP administration to treat IVD degeneration and to ameliorate IVD-associated chronic low back pain.

Mass customization design of engineer-to-order products using Benders’ decomposition and bi-level stochastic programming

Leveraging product differentiation and mass production efficiency in mass customization basically entails a configure-to-order paradigm. In the engineer-to-order (ETO) business, however, companies build unique products in response to `foreseeable' customer specifications. The key challenge of ETO mass customization lies in the complexity of accommodating future design changes when customers are involved in customizing design specifications. This paper proposes a two-stage, bi-level stochastic programming framework to tackle ETO mass customization. At the first stage, product platform configuration is integrated with production reconfiguration, which is formulated as a shortest path problem with resource constraints (SPPRC) to optimize production delays within the capabilities of the process platform. Benders' decomposition algorithm is applied to solve this optimal configuration problem owing to its high computational efficiency. The second stage scrutinizes the optimal configuration resulting from the first stage for scaling optimization of design parameters (DPs) for each module. All DPs are differentiated by standard or customizable DPs. A bi-level stochastic program is implemented to leverage conflicting goals between the producer (leader) and consumer (follower) surpluses. As a result, ETO customization design is anchored with optimal values of standard DPs and optimal value ranges of customizable DPs. A case study of ship engine and power generator ETO design is presented, demonstrating the feasibility and potential of the ETO mass customization framework.

Experimental investigation of the effect of compression ratio and injection pressure in a direct injection diesel engine running on Karanj methyl ester

Being a fuel of a different origin, the standard design parameters of a diesel engine are not optimum for Karanj methyl ester (KME). This study aims at finding the effect of the engine design parameters, viz. compression ratio (CR) and fuel injection pressure (IP) jointly on the performance and emissions. Brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE) were considered for performance evaluation, and emission analysis was done for un-burnt hydrocarbon, carbon monoxide (CO), carbon dioxide (CO2), oxides of nitrogen (NO x ), exhaust gas temperature and smoke opacity with KME as the fuel. Comparison of performance and emission was done for different values of CR along with IP to find the optimum combination for operating engine with KME. It is found that the combined increase in CR and IP increases the BTE and reduces BSFC while having lower emissions. For small-sized direct injection constant speed engines used for agricultural applications (3.5 kW), the optimum combination was found to be CR of 18 with IP of 250 bar.

Modeling of Tubing Pickling in Conjunction With Acidizing Treatments

Summary Pickling well tubulars to prevent pumping unwanted materials into the formation is an issue that should be decided on an individual-job basis. Acid pickling of tubing is a process of flow in a tube or an annulus with heterogeneous reactions occurring at the wall of the tube. The reacting solid species at the wall are primarily mill scale and other types of inorganic scale. The fluids injected for pickling are usually strong acid solutions [hydrochloric acid (HCl)] but also may include surfactants, organic solvents, and gelled solutions to aid in lifting solids from the wellbore. Thus, the process is a complex one involving several reactions and perhaps multiple stages of fluids. Tubing pickling is an essential part of well-stimulation treatments if the main acid is to be bullheaded. Standard design parameters for a pickle treatment depend on experience and personal judgment. It appears that the standard pickle-treatment design is overestimating the required volume of pickling acid. Field data indicated that excessive acid volumes were used for tubing pickling because large returns of unreacted (live) acid were recovered at the surface. Careful analysis of flowback samples obtained from several deep gas wells showed that only a fraction of the acid was consumed by mill scale and other tubing contaminants. In this paper, proposed mechanisms are presented to explain the behavior of acid contact with the tubing and a mathematical model is developed to predict acid consumption and dissolution of tubular contaminants. The model applies to the bullheading case where the acid is pumped down the tubing and then flowed back to the surface. The model considers the reaction of acid with mill scale (Fe3O4). The equations formulated are solved numerically to predict the concentrations of major chemical species in the well flowback samples. Such a model is extremely valuable in optimizing future pickling treatments. The acid volume needed for pickling operations can be reduced significantly, and other improvements can be made without extensive and costly field testing. Finally, recommendations are given to design acid-pickling treatments better.

Experimental investigation of the effect of compression ratio and injection pressure in a direct injection diesel engine running on Jatropha methyl ester

Being a fuel of different origin, the standard design parameters of a diesel engine may not be suitable for Jatropha methyl ester (JME). This study targets at finding the effects of the engine design parameters viz. compression ratio (CR) and fuel injection pressure (IP) jointly on the performance with regard to fuel consumption (BSFC), brake thermal efficiency (BTHE) and emissions of CO, CO2, HC, NOx and Smoke opacity with JME as fuel. Comparison of performance and emission was done for different values of compression ratio along with injection pressure to find best possible combination for operating engine with JME. It is found that the combined increase of compression ratio and injection pressure increases the BTHE and reduces BSFC while having lower emissions. For small sized direct injection constant speed engines used for agricultural applications (3.5 kW), the optimum combination was found as CR of 18 with IP of 250 bar.

Optimum Design of a Composite Helical Spring by Multi-criteria Optimization

A new methodology for the optimum design of composite helical springs with braided fibrous reinforcement is presented in this article. A multi-objective evolutionary algorithm is implemented to optimize two conflicting goals: minimize mass and maximize stiffness. Several design variables that have an influence on the mechanical properties of the spring must be considered: the braiding angle, number of plies and the standard design parameters of a helical spring. Design goals are set such as for standard metallic springs: equivalent mechanical performance, mass reduction, and comparable cost. Three different braided reinforcements in carbon, kevlar, and glass were analyzed with the same epoxy matrix. In helical springs, shear plays the most important role on spring performance. Taking into account the shear properties of braided composites and a series of technological constraints, a range of composite springs was devised, among which an optimal spring was selected for an automotive application, namely to replace the metallic spring of the suspension of a sport utility vehicle.

Determining [formula omitted] in ττ fusion to SUSY Higgs bosons at a photon collider

We investigate ττ fusion to light h and heavy H and A Higgs bosons in the Minimal Supersymmetric Standard Model (MSSM) at a photon collider as a promising channel for measuring large values of tanβ. For standard design parameters of a photon collider an error Δtanβ∼1, uniformly for tanβ≳10, is expected from this theoretical study, improving on complementary measurements at the LHC and e+e− linear colliders, and encouraging detailed experimental simulations.

New Appoaches to Inspection Planning of Fatigue Damaged Offshore Platforms

The present paper summarizes the results of research and development efforts over the last approximately five years to develop simplified and practically applicable approaches for reliability and risk based inspection planning. These efforts have led to the development of a generic inspection planning approach. Following the approach the fatigue sensitive details are categorized and described generically according to standard design parameters such as the Fatigue Design Factor (FDF) and the SN curve. When a measure of the structural consequences of fatigue failure e.g. the RSR and the corresponding probability of structural collapse given fatigue failure of the considered detail are known, generic inspection plans may derived as a function of the generic parameters together with the relative cost of inspections, repairs and failures. Due to the simplicity of the format of the developed inspection plans, the proposed approach has a high potential to be used in codes for the design and maintenance of steel structures. The validity of the proposed approach is illustrated through a study regarding inspection planning of a tri-pod offshore structure where generic inspection plans are obtained using two approximations, namely assuming equidistant inspection intervals and using constant thresholds for the annual probability of failure.

Structural Evaluation of Box Culverts

Corrugated‐metal box culverts are employed as replacements for short‐span bridges. As a result of increasing use, there is a great demand for establishing a rational design procedure for these culverts. The available design procedures are based on experience or mathematical modeling. Only a limited number of attempts have been made to verify these design techniques with full‐scale field tests. Three corrugated‐metal box culverts were fully instrumented and field‐tested under similar backfill conditions and live loads. The first culvert was bulb‐angle‐rib‐reinforced corrugated aluminum; the second was rib‐reinforced corrugated steel; and the third was corrugated‐rib‐reinforced corrugated steel. The collected data were evaluated using a finite element analysis, and the applicability of standard design parameters was determined. Maximum bending moments obtained from field tests were compared to plastic moments calculated according to American Association of State Highway and Transportation Officials (AASHTO) specifications. It was concluded that the design for these types of structures can be improved if (1) Composite action is assumed; (2) thrust forces are included in design; and (3) construction procedures are controlled. The AASHTO specifications were conservative for rib‐reinforced, corrugated‐metal culverts.