scholarly journals A Circuit-Model-Navigated Design Process and Efficiency Estimation for Short-Circuited Self-Excited EBG Resonator Antenna

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Mehdi Hosseini
Keyword(s):  
Design Process ◽  
Circuit Model ◽  
Manufacturing Processes ◽  
Efficient Design ◽  
Computationally Efficient ◽  
Efficiency Estimation ◽  
Degree Of Confidence ◽  
Small Antenna ◽  
High Degree ◽  
Cap Method

The paper presents a circuit model for the computationally efficient design of a planar Short-Circuited Self-Excited EBG Resonator Antenna (SC SE-EBG-RA). To this purpose, the same circuit model previously presented for the Open-Circuited version of the antenna is modified to be applicable to the SC version. Detailed HFSS modeling and simulation corroborate the accuracy of the model in predicting the antenna resonance. The efficiency of the designed antenna is calculated by a simulated Wheeler Cap Method (WCM) and is compared with the standard efficiency given by the numerical analyzer. The EM modeling is arranged so as to incorporate the effects of the SMA connector, discontinuities, and the WC, emulating a real WC measurement and yielding a high degree of confidence in the results. Overall, a small antenna sized0.34λ×0.30λ×0.03λwith 93% verified efficiency is achieved, which is also compiled with affordable manufacturing processes.

Einbringen von Gewinden in SLM-Bauteile*/Insertion of threads into SLM components – Reliable strategy for inserting threads into additively manufactured components

2019 ◽  
Vol 109 (01-02) ◽  
pp. 24-29
Author(s):  
E. Abele ◽  
T. Scherer ◽  
F. Geßner ◽  
M. Weigold
Keyword(s):  
Additive Manufacturing ◽  
Selective Laser Melting ◽  
Downstream Processing ◽  
Manufacturing Processes ◽  
Laser Melting ◽  
Manufacturing Costs ◽  
Process Reliability ◽  
High Degree ◽  
Design Freedom ◽  
Processing Steps

Additive Fertigungsverfahren zeichnen sich durch große Gestaltungsfreiheit aus, welche die Herstellung komplexer Bauteile ermöglicht. Angesichts hoher Fertigungskosten ist die Prozesssicherheit nachgeordneter Bearbeitungsschritte (wie zum Beispiel die Gewindefertigung) von großer Bedeutung. Der Artikel stellt die Ergebnisse einer Untersuchungsreihe vor, die unterschiedliche Ansätze der Gewindefertigung in Bauteilen aus Stahl behandelt, die mittels Selektivem Laserschmelzverfahren gefertigt wurden.   Additive manufacturing processes are characterized by a high degree of design freedom to enablet the production of complex components. To reduce manufacturing costs, the process reliability of downstream processing steps (e. g. thread production) is of great importance. This article presents the results of a series of investigations dealing with different approaches to thread production in steel components manufactured by selective laser melting

Determination of Sample Size in Service Inspection

1997 ◽  
Vol 119 (1) ◽  
pp. 57-60
Author(s):  
S. Qin ◽  
G. E. O. Widera
Keyword(s):  
Sample Size ◽  
Large Volume ◽  
Analysis Method ◽  
Degree Of Confidence ◽  
Impossible Task ◽  
The Mean ◽  
High Degree ◽  
Service Inspection ◽  
False Rejection

When performing inservice inspection on a large volume of identical components, it becomes an almost impossible task to inspect all those in which defects may exist, even if their failure probabilities are known. As a result, an appropriate sample size needs to be determined when setting up an inspection program. In this paper, a probabilistic analysis method is employed to solve this problem. It is assumed that the characteristic data of components has a certain distribution which can be taken as known when the mean and standard deviations of serviceable and defective sets of components are estimated. The sample size can then be determined within an acceptable assigned error range. In this way, both false rejection and acceptance can be avoided with a high degree of confidence.

scholarly journals An Evaluation-Driven Design Process for Exhibitions

2017 ◽  
Author(s):  
Wolfgang Leister ◽  
Ingvar Tjøstheim ◽  
Göran Joryd ◽  
Michel de Brisis ◽  
Syver Lauritzsen ◽  
...  
Keyword(s):  
Design Process ◽  
Informal Education ◽  
Graphical Representation ◽  
Working Relationship ◽  
Efficient Design ◽  
Learning Game ◽  
Science Centre ◽  
Science Centres

Museums and Science Centres are informal education environments that intend to engage the visitors with their exhibits. We present an efficient design process that allows an improved working relationship between museum practitioners, exhibition designers, and visitors. We present the principles and a graphical representation based on the Engagement Profile from previous work. Elements of the design process are evaluated using a learning game at the science centre Engineerium. The evaluation is based on a study with over five hundred visitors to the science centre.

A model-driven framework for multi-paradigm modeling and holistic simulation of healthcare systems

SIMULATION ◽  
2017 ◽  
Vol 94 (3) ◽  
pp. 235-257 ◽  
Author(s):  
Ignace Djitog ◽  
Hamzat O Aliyu ◽  
Mamadou K Traoré
Keyword(s):  
Model Transformation ◽  
Healthcare Systems ◽  
Integrative Approach ◽  
Efficient Design ◽  
Model Driven ◽  
Dynamic Update ◽  
Modeling Methodology ◽  
Multiple Levels ◽  
High Degree ◽  
Answering Questions

The domain of healthcare is characterized by a high degree of complexity and a diversity of perspectives, and modelers are often confronted with the challenge of formulating a simulation model that captures this complexity in a systematic and manageable manner. Most often, the diverse perspectives of healthcare systems are studied in isolation and using specific formalisms. As it turns out, answering questions concerning behavioral properties of the overall system becomes difficult and therefore not sufficient for an efficient design and analysis of the system under study. In this article, we propose a framework for multi-paradigm modeling and holistic simulation of healthcare systems. We present a modeling methodology with a plethora of formalisms to allow the modeler to choose an appropriate formalism at a given level of abstraction while model transformation relates the different formalisms. Furthermore, we develop an integrative approach for the interactions between models of different perspectives through dynamic update of model output-to-parameter integration during concurrent simulations. Such an approach provides multiple levels of explanation for the same system, while offering, at the same time, an integrated view of the whole. The framework has successfully been applied to study part of the Nigerian healthcare system.

Advanced aircraft performance analysis

2018 ◽  
Vol 90 (4) ◽  
pp. 627-638 ◽  
Author(s):  
Marc Immer ◽  
Philipp Georg Juretzko
Keyword(s):  
Performance Analysis ◽  
Design Process ◽  
Performance Optimization ◽  
Electric Propulsion ◽  
Vertical Plane ◽  
Aircraft Design ◽  
Efficient Design ◽  
Content Type ◽  
Aircraft Performance ◽  
Hybrid Electric

Purpose The preliminary aircraft design process comprises multiple disciplines. During performance analysis, parameters of the design mission have to be optimized. Mission performance optimization is often challenging, especially for complex mission profiles (e.g. for unmanned aerial vehicles [UAVs]) or hybrid-electric propulsion. Therefore, the purpose of this study is to find a methodology that supports aircraft performance analysis and that is applicable to complex profiles and to novel designs. Design/methodology/approach As its core element, the developed method uses a computationally efficient C++ software “Aircraft Performance Program” (APP), which performs a segment-based mission computation. APP performs a time integration of the equations of motion of a point mass in the vertical plane. APP is called via a command line interface from a flexible scripting language (Python). On top of APP’s internal radius of action optimization, state-of-the-art optimization packages (SciPy) are used. Findings The application of the method to a conventional climb schedule shows that the definition of the top of climb has a significant influence on the resulting optimum. Application of the method to a complex UAV mission optimization, which included maximizing the radius of action, was successful. Low computation time enables to perform large parametric studies. This greatly improves the interpretation of the results. Research limitations/implications The scope of the paper is limited to the methodology that allows for advanced performance analysis at the conceptual and preliminary design stages with an emphasis on novel propulsion concepts. The methodology is developed using existing, validated methods, and therefore, this paper does not contain comprehensive validation. Other disciplines, such as cost analysis, life-cycle assessment or market analysis, are not considered. Practical implications With the proposed method, it is possible to obtain not only the desired optimum mission performance but also off-design performance of the investigated design. A thorough analysis of the mission performance provides insight into the design’s capabilities and shortcomings, ultimately aiding in obtaining a more efficient design. Originality/value Recent developments in the area of hybrid or hybrid-electric propulsion systems have shown the need for performance computation tools aiding the related design process. The presented method is especially valuable when novel design concepts with complex mission profiles are investigated.

scholarly journals A crystallographic study of crystalline casts and pseudomorphs from the 3.5 Ga Dresser Formation, Pilbara Craton (Australia)

2018 ◽  
Vol 51 (4) ◽  
pp. 1050-1058 ◽  
Author(s):  
Fermin Otálora ◽  
A. Mazurier ◽  
J. M. Garcia-Ruiz ◽  
M. J. Van Kranendonk ◽  
E. Kotopoulou ◽  
...  
Keyword(s):  
High Temperature ◽  
Geological History ◽  
X Ray Diffraction ◽  
Mineral Phase ◽  
X Ray ◽  
Crystallographic Study ◽  
History Of ◽  
Degree Of Confidence ◽  
High Degree ◽  
Pilbara Craton

Crystallography has a long history of providing knowledge and methods for applications in other disciplines. The identification of minerals using X-ray diffraction is one of the most important contributions of crystallography to earth sciences. However, when the crystal itself has been dissolved, replaced or deeply modified during the geological history of the rocks, diffraction information is not available. Instead, the morphology of the crystal cast provides the only crystallographic information on the original mineral phase and the environment of crystal growth. This article reports an investigation of crystal pseudomorphs and crystal casts found in a carbonate-chert facies from the 3.48 Ga-old Dresser Formation (Pilbara Craton, Australia), considered to host some of the oldest remnants of life. A combination of X-ray microtomography, energy-dispersive X-ray spectroscopy and crystallographic methods has been used to reveal the original phases of these Archean pseudomorphs. It is found with a high degree of confidence that the original crystals forming in Archean times were hollow aragonite, the high-temperature polymorphs of calcium carbonate, rather than other possible alternatives such as gypsum (CaSO4·2H20) and nahcolite (NaHCO3). The methodology used is described in detail.

A Decomposition Method for Concurrent Design of Mixed Discrete/Continuous Systems

1993 ◽  
Author(s):  
Jeffrey M. Ford ◽  
Christina L. Bloebaum
Keyword(s):  
Design Process ◽  
Decomposition Method ◽  
Organizational Design ◽  
Method Development ◽  
Minimum Weight ◽  
Optimization Methods ◽  
Continuous Systems ◽  
Computationally Efficient ◽  
Subspace Optimization ◽  
Design Variables

Abstract Interest in Concurrent Engineering (CE) has increased as industry looks for more efficient means of product design. Design optimization methods that facilitate the CE approach are an important aspect of current research. Among the methods that have been proposed is the Concurrent Subspace Optimization (CSSO) method, which allows the optimization problem to be decomposed into coupled subproblems. These subproblems may correspond to the different disciplines involved in the design process or to participating organizational design or manufacturing groups. The decomposition allows each discipline to apply their own optimization criteria to the problem. While this method may not be as computationally efficient as other methods, it allows the design process to conform to the departmental divisions that already exist in industry. The method development to date has focused on continuous systems only. However, problems that can not be modeled as continuous systems, such as those involving the placement of active controllers in CSI applications, would benefit from a method that allows the use of discrete parameters. The paper presents a decomposition method (based on CSSO) for the optimal design of mixed discrete/continuous systems. The method is applied to the design of a composite plate for minimum weight, with design variables contributed from sizing variables (continuous) and material combinations (discrete).

Methodology Used to Calculate Naval Compensated Gross Tonnage Factors

2003 ◽  
Vol 19 (01) ◽  
pp. 22-28
Author(s):  
John Craggs ◽  
Damien Bloor ◽  
Brian Tanner ◽  
Hamish Bullen
Keyword(s):  
Performance Improvement ◽  
Acquisition Strategies ◽  
Degree Of Confidence ◽  
High Degree ◽  
Two Sectors

Internationally accepted compensation factors exist for the main commercial ship types, but as yet there are no reliable factors for some unusual ship types or naval vessels. There have been at least two attempts to develop factors for U.S. naval vessels, but at present there is no agreement regarding the validity of the proposed factors. The aim of this paper is to outline the methodology developed to determine compensated gross tonnage (CGT) factors for U.K. naval vessels. This ongoing area of work, instigated and funded by the U.K. Ministry of Defence (MoD) and carried out by First Marine International, has been undertaken in partnership with leading U.K. and European shipbuilders. Three different methods have been used to calculate factors for a Type 23 frigate and an auxiliary oiler replenishment vessel. There was a good correlation between the factors derived by each method, giving the researchers a high degree of confidence in the principal weight-based methodology. The derivation of naval CGT factors and the subsequent analysis will assist MoD to estimate construction budgets, improve acquisition strategies, and quickly assess the implications of changes on unit procurement costs. U.K. naval shipbuilders will benefit from the ability to benchmark themselves against other naval and commercial shipbuilders and assess opportunities for performance improvement. The paper also discusses disparities in productivity between naval and commercial shipbuilders. It puts forward the view that fundamental differences between the two sectors will mean naval shipbuilders will inherently exhibit a lower level of productivity than commercial yards of similar technology.

Computationally Efficient and Effective Machine Learning Model Using Time Series Data in Different Prediction Problems

2021 ◽  
pp. 218-233
Author(s):  
Dwiti Krishna Bebarta ◽  
Birendra Biswal
Keyword(s):  
Machine Learning ◽  
Predictive Models ◽  
Time Series Data ◽  
Predictive Analytics ◽  
Learning Model ◽  
Series Data ◽  
Computationally Efficient ◽  
Machine Learning Model ◽  
High Degree ◽  
Prediction Problems

Automated feature engineering is to build predictive models that are capable of transforming raw data into features, that is, creation of new features from existing ones on various datasets to create meaningful features and examining their effect on planned model performances on various parameters like accuracy, efficiency, and prevent data leakage. So the challenges for experts are to plan computationally efficient and effective machine, learning-based predictive models. This chapter will provide an imminent to the important intelligent techniques that could be utilized to enhance predictive analytics by using an advanced form of the predictive model. A computationally efficient and effective machine learning model using functional link artificial neural network (FLANN) is discussed to design for predicting the business needs with a high degree of accuracy for the traders or investors. The performance of the models using FLANN is encouraging when scientifically analyzed the experimental results of the model using different statistical analyses.

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