Multidisciplinary Design Research Articles

Towards processual understanding of knowledge boundaries: an ethnographic examination of how professionals (mis-)align, compete, and collaborate

PurposeExtant literature tends to consider knowledge boundaries as a necessary property of interdisciplinary work. Knowledge boundaries are, thus, reified and treated as something to be traversed, transcended or otherwise negotiated. There is, however, very little work that closely examines the process of emergence of boundaries. The purpose of this paper is to critically consider the emergence, stabilization and dissolution of knowledge boundaries among experts during the design stage of a building project to understand whether knowledge boundaries are as delineated and predictable as the literature makes them out to be.Design/methodology/approachA process-based, ethnographic study of a construction project is used. Building on a large data set collected over 13 months of research, this paper closely examines collaborative work around one specific issue during design development work that tripped up collaboration of the multidisciplinary and inter-organizational design team.FindingsKnowledge boundaries do not exist based on differences of substance among groups (e.g. being an engineer vs being an architect) but rather that they are a function of divergent constellations of interests, work tools and practical concerns. While holding binding powers, they evolve in the face of alignments and misalignments, agreements and conflicts. As interests shift, concerns unfold and tools are dropped or used; boundaries emerge or dissolve.Originality/valueA processual view of knowledge boundaries is advanced by demonstrating how they evolve in face of convergent (or divergent) work tools, practical concerns and interests. Existing research tends to equate knowledge boundaries with occupational/professional differences directly, but this paper demonstrates that work across expertise domains does not generate boundaries by itself. Resulting theoretical contributions are twofold: first, the current understanding of knowledge boundaries is refined by explaining how and why they emerge and dissolve across and within specialist knowledge domains, and second, the role of power and politics in this process is empirically foregrounded, highlighting how constellations of interests can lead to dynamic alliances or divisions.

A Software Engineering Framework for Reusable Design of Personalized Serious Games for Health: Development Study.

The use of serious games in health care is on the rise, as these games motivate treatment adherence, reduce treatment costs, and educate patients and families. However, current serious games fail to offer personalized interventions, ignoring the need to abandon the one-size-fits-all approach. Moreover, these games, with a primary objective other than pure entertainment, are costly and complex to develop and require the constant involvement of a multidisciplinary team. No standardized approach exists on how serious games can be personalized, as existing literature focuses on specific use cases and scenarios. The serious game development domain fails to consider any transfer of domain knowledge, which means this labor-intensive process must be repeated for each serious game. We proposed a software engineering framework that aims to streamline the multidisciplinary design process of personalized serious games in health care and facilitates the reuse of domain knowledge and personalization algorithms. By focusing on the transfer of knowledge to new serious games by reusing components and personalization algorithms, the comparison and evaluation of different personalization strategies can be simplified and expedited. In doing so, the first steps are taken in advancing the state of the art of knowledge regarding personalized serious games in health care. The proposed framework aimed to answer 3 questions that need to be asked when designing personalized serious games: Why is the game personalized? What parameters can be used for personalization? and How is the personalization achieved? The 3 involved stakeholders, namely, the domain expert, the (game) developer, and the software engineer, were each assigned a question and then assigned responsibilities regarding the design of the personalized serious game. The (game) developer was responsible for all the game-related components; the domain expert was in charge of the modeling of the domain knowledge using simple or complex concepts (eg, ontologies); and the software engineer managed the personalization algorithms or models integrated into the system. The framework acted as an intermediate step between game conceptualization and implementation; it was illustrated by developing and evaluating a proof of concept. The proof of concept, a serious game for shoulder rehabilitation, was evaluated using simulations of heart rate and game scores to assess how personalization was achieved and whether the framework responded as expected. The simulations indicated the value of both real-time and offline personalization. The proof of concept illustrated how the interaction between different components worked and how the framework was used to simplify the design process. The proposed framework for personalized serious games in health care identifies the responsibilities of the involved stakeholders in the design process, using 3 key questions for personalization. The framework focuses on the transferability of knowledge and reusability of personalization algorithms to simplify the design process of personalized serious games.

A self-adaptive local diversity-preserving NSGA-II for the multidisciplinary design optimization of a miniaturized supersonic rocket

The miniaturized supersonic rocket or missile is an innovative concept most notably characterized by its small caliber, short length, and high flight speed. Tightly coupled design parameters and constrained objectives bring high complexity to launch safety assessments. The commonly used heuristic algorithm NSGA-II cannot address this complexity with its original density estimation strategy. In this paper, a multidisciplinary design optimization (MDO) based on a multidisciplinary feasible (MDF) architecture is established and simplified according to specific design requirements. The design system includes one coupled numerical model, two drivers, and six disciplines. As an optimizer for an MDO problem, multi-objective evolutionary algorithms (MOEAs) with heuristic features are very conducive to exploring the performance of complex rocket systems. The coupling relationship between the design variables of a small dual-chamber rocket is complex, and its optimal design is challenging to obtain empirically by traditional methods. Optimizing its propulsion performance and launch safety is imperative. For engineering designs, the convergence process of algorithms is often passive with a high degree of randomness, and the diversity of the final results is difficult to guarantee. This paper improves the Pareto front's diversity in designing a miniaturized supersonic rocket by using a self-adaptive local diversity-preserving NSGA-II (SLDNSGA-II) in an MDO framework with an active control strategy.

Art education through the sustainable design of learning spaces

Art education is a valuable tool for achieving quality education by fostering creativity and an appreciation of learning and culture. Well-designed learning spaces are conducive to art learning. The COVID-19 pandemic prompted the author to review the design of learning spaces employed in previous pandemics and other outdoor learning spaces developed over time. A project was carried out at the university level with future secondary school art teachers to design a sustainable art learning space as a multidisciplinary exercise, combining art, architecture and design. Solutions were analysed across multiple criteria. The results demonstrate the suitability of the proposed activity to promote critical creativity among students in Tenerife in the Canary Islands. This type of project in art education is essential for academics and educators so that they become involved in sustainability issues so present in contemporary life.

Research on MDO of Ship Propulsion Shafting Dynamics Considering the Coupling Effect of a Propeller-Shafting-Hull System

Abstract Dynamic designs for ship propulsion shafting can be categorised as complex multi-disciplinary coupling systems. The traditional single disciplinary optimisation design method has become a bottleneck, restricting the further improvement of shafting design. In this paper, taking a complex propulsion shafting as the object, a dynamic analysis model of the propeller-shafting-hull system was established. In order to analyse the coupling effect of propeller hydrodynamics on shafting dynamics, the propeller’s hydrodynamic force in the wake flow field was calculated as the input for shafting alignment and vibration analysis. On this basis, the discipline decomposition and analysis of the subdisciplines in design of shafting dynamics were carried out. The coupling relationships between design variables in the subdisciplines were studied and the Multi-disciplinary Design Optimisation (MDO) framework of shafting dynamics was established. Finally, taking the hollowness of the shaft segments and the vertical displacement of bearings as design variables, combined with the optimal algorithm, the MDO of shafting dynamics, considering the coupling effect of the propeller-shafting-hull system, was realised. The results presented in this paper can provide a beneficial reference for improving the design quality of ship shafting.

Building Performance Optimization throughout the Design–Decision Process with a Holistic Approach

Building performance optimization throughout the design–decision process has not been well defined, especially in holistic approaches that require multilevel integration. For this, it is essential to ensure coexistence between different analysis programs such as three-dimensional (3D), energy, and computational fluid dynamics (CFD) models that can be applied on a single platform such as building information modeling (BIM). This research aims, first, to define and document a holistic design approach to building performance optimization concerning energy usage by employing the BIM platform and, second, to underline interoperability and data exchange between current technology and commercially available software from different vendors. Therefore, the novelty of this study is to serve a systematic, multiobjective, and multicriterion optimization of building performance with a holistic approach in the BIM platform. The holistic design approach is for a multidisciplinary design process including three stages (conceptual, schematic, and detailed) that cover different optimization criteria (building envelope design, occupants’ comfort conditions, and building’ energy consumption). The proposed method aims to generate, evaluate, develop, and utilize a 3D model during the different design stages concerning the model’s level of details and included information, which underlines the usage of 3D model-related software and sharing data among the design stages. A BIM-based method is developed through the case study of a hypothetical, two-story building (domestic dwelling) by identifying the activities of each design stage. With the implementation of the proposed method, the result shows a predicted energy saving of up to 75%, with a detailed energy analysis placing the building energy performance in the “A” class (annual energy consumption 17,865 kW · h). At last, based on the authors’ experience during the study, it is time- and effort-saving to have interoperability between BIM tools.

Adjoint-Based High-Fidelity Concurrent Aerodynamic Design Optimization of Wind Turbine

To evaluate novel turbine designs, the wind energy sector extensively depends on computational fluid dynamics (CFD). To use CFD in the design optimization process, where lower-fidelity approaches such as blade element momentum (BEM) are more popular, new tools to increase the accuracy must be developed as the latest wind turbines are larger and the aerodynamics and structural dynamics become more complex. In the present study, a new concurrent aerodynamic shape optimization approach towards multidisciplinary design optimization (MDO) that uses a Reynolds-averaged Navier–Stokes solver in conjunction with a numerical optimization methodology is introduced. A multidisciplinary design optimization tool called DAFoam is used for the NREL phase VI turbine as a baseline geometry. Aerodynamic design optimizations in terms of five different schemes, namely, cross-sectional shape, pitch angle, twist, chord length, and dihedral optimization are conducted. Pointwise, a commercial mesh generator is used to create the numerical meshes. As the adjoint approach is strongly reliant on the mesh quality, up to 17.8 million mesh cells were employed during the mesh convergence and result validation processes, whereas 2.65 million mesh cells were used throughout the design optimization due to the computational cost. The Sparse Nonlinear OPTimizer (SNOPT) is used for the optimization process in the adjoint solver. The torque in the tangential direction is the optimization’s merit function and excellent results are achieved, which shows the promising prospect of applying this approach for transient MDO. This work represents the first attempt to implement DAFoam for wind turbine aerodynamic design optimization.

Aerodynamic and structural multidisciplinary optimization design method of fan rotors based on blade curvature constraints

The optimization design of the actual fan/compressor rotors is a multidisciplinary problem. The aerodynamics and strength multidisciplinary optimization design of the fan/compressor rotors can improve the aerodynamic performance of rotors as much as possible under the condition of satisfying the structural strength requirements. However, the conventional multidisciplinary optimization of aerodynamics and structures will significantly increase the amount of computation cost and time period. Thus, it is difficult for conventional multidisciplinary optimization methods to be used in real-world engineering practices. In order to reduce the computational burden and time cost of the multidisciplinary optimization design, this paper firstly proposes a multidisciplinary optimization design method for rotors based on blade curvature constraints. In the optimization, the self-organizing map (SOM) method is applied to analyze and extract the constraint value of the blade curvature. And the blade curvature constraint value is used as a penalty function instead of the time-consuming high-fidelity FEM, which greatly reduces the computational cost and runtime of the multidisciplinary optimization. Besides, the Free-form deformation (FFD) method is adopted to realize the flexible deformation of the three-dimensional blade with the smallest number of design variables and polynomial chaos Kriging is used as a surrogate model for aerodynamic performance prediction in the optimization process. The method verification and mechanism analysis are carried out by studying a fan rotor. Data mining of FEM samples shows that, in the optimization design space, the maximum spanwise curvature of the blade is monotonically related to the maximum stress of the blade. And the maximum streamwise curvature, maximum spanwise slope, maximum streamwise slope, and maximum thickness of the blade have no related relationship with the maximum stress of the blade. Compared with the conventional multidisciplinary optimization design method based on the surrogate models of high-fidelity computational fluid dynamics (CFD) and finite element method (FEM), the time cost of the multidisciplinary optimization design method based on curvature constraints is reduced by 10 times, and the time cost of the multidisciplinary optimization is significantly reduced. The results show that, in terms of structural performance, the maximum stress of the aerodynamic optimization method without blade curvature constraints is 426 MPa, which exceeds the yield limit of aluminum alloy material (420 MPa), and the maximum stress of the multidisciplinary optimization design with blade curvature constraints proposed in this paper is 344 MPa. In terms of aerodynamic performance, the isentropic efficiency of the aerodynamic optimization method without blade curvature constraints and the method proposed in this paper are increased by 2.1% and 1.8%, respectively. Therefore, the proposed method reduces the maximum stress of the blade by 19.5% with little influence on the aerodynamic performance.

Assessment of Potential Commercial Success of Business Jets with Natural Laminar Flow

The present research investigates the potential application of the natural laminar flow wing technology to business jet market segments from light to long-range jets. A database of existing business jets was generated to determine the range extension as a potential driver of customer interest. A conceptual design of several configurations for each market segment was performed to investigate potential improvements in the aircraft flight range, operating costs, and price changes using the technology. An initial sizing module and a low-fidelity multidisciplinary design optimization were used to size all aircraft. Results demonstrated a 13–30% increase in the flight range depending on the aircraft concept. Long-range jets with natural laminar flow could not achieve significant range extension due to a combination of the design airspeed and maintenance costs. A rapid increase in acquisition prices for all aircraft suggested that super-midsize and large jets that combine relatively low empty weight and high range extension could be more favorable options compared to other segments, but a significant reduction of acquisition costs and an increase in operating flight hours are required to make the technology implementation successful.

A collaborative multidisciplinary design methodology for additive manufacturing with a left-handed mouse as a case study

A collaborative multidisciplinary design methodology for additive manufacturing with a left-handed mouse as a case study

Quantifying and mitigating uncertainties in design optimization including off-the-shelf components: Application to an electric multirotor UAV

This article proposes an approach to quantify and manage uncertainty in the conceptual design of aerial vehicles. A growing number of aerial vehicles, such as unmanned aerial vehicles (UAVs), are being wholly or partly designed with off-the-shelf components to streamline development and certification costs. The design optimization of systems typically relies on component design models in the continuous domain. In addition to the inaccuracies in the design models, the continuous domain condition is inconsistent with the finite number of components available in the market. This inconsistency yields uncertainty about the actual characteristics of the components defined by the continuous design process, hence inaccurate performance predictions at the system's level. The proposed approach is developed within the scope of the conceptual design of multirotor UAVs and covers the uncertainties related to both the design models and off-the-shelf components availability. Simple criteria are established to determine the importance of uncertainties according to the density of products in an off-the-shelf component database. The uncertainties are propagated through the system's models to evaluate the variance of the outputs and identify the most critical design parameters. A multidisciplinary design optimization framework enabling custom, off-the-shelf, and hybrid design is introduced and illustrated with a multirotor UAV case study. This case study demonstrates that switching from a custom design to an off-the-shelf selection for the most critical component, namely the propeller, results in a 69% reduction in the standard deviation of estimated hover endurance. The results obtained demonstrate that the proposed approach can contribute to the emergence of future aerial vehicles and systems that must meet demanding economic and performance targets by combining custom and off-the-shelf components in their design.

A multi-fidelity model management framework for multi-objective aerospace design optimisation

This paper presents a multi-fidelity meta-modelling and model management framework designed to efficiently incorporate increased levels of simulation fidelity from multiple, competing sources into early-stage multidisciplinary design optimisation scenarios. Phase specific/invariant low-fidelity physics-based subsystem models are adaptively corrected via iterative sampling of high(er)-fidelity simulators. The correction process is decomposed into several distinct parametric/non-parametric stages, each leveraging alternate aspects of the available model responses. Globally approximating surrogates are constructed at each degree of fidelity (low, mid, and high) via an automated hyper-parameter selection and training procedure. The resulting hierarchy drives the optimisation process, with local refinement managed according to a confidence-based multi-response adaptive sampling procedure, with bias given to global parameter sensitivities. An application of this approach is demonstrated via the aerodynamic response prediction of a parametrized re-entry vehicle, subjected to a static/dynamic parameter optimisation for three separate single-objective problems. It is found that the proposed data correction process facilitates increased efficiency in attaining a desired approximation accuracy relative to a single-fidelity equivalent model. When applied within the proposed multi-fidelity management framework, clear convergence to the objective optimum is observed for each examined design optimisation scenario, outperforming an equivalent single-fidelity approach in terms of computational efficiency and solution variability.

A Technology-Supported Guidance Model to Increase the Flexibility, Quality, and Efficiency of Nursing Education in Clinical Practice in Norway: Development Study of the TOPP-N Application Prototype

The challenges of nursing shortage in the nursing profession and of limited nursing educational capacity in nursing education in clinical practice need to be addressed to ensure supply according to the demand of these professionals. In addition, communication problems among nursing students, nurse educators, and nurse preceptors; variations in the guidance competence of nurse preceptors; and limited overview from nurse educators on nursing students' clinical practice are common challenges reported in several research studies. These challenges affect the quality of nursing education in clinical practice, and even though these problems have been highlighted for several years, a recent study showed that these problems are increasing. Thus, an approach is required to ensure the quality of nursing education in clinical practice. We aimed to develop a guidance and assessment application to meet the challenges reported in clinical practice. The application intended to increase the flexibility, quality, and efficiency of nursing education in clinical practice. Furthermore, it intended to increase interactive communication that supports guidance and ensure structured evaluation of nursing students in clinical practice. This study employed a multidisciplinary user-participatory design. Overall, 23 stakeholders from the project team (ie, 5 researchers, 2 software developers, 1 pedagogical advisor, and 15 user representatives [4 educators, 6 preceptors, and 5 students]) participated in a user-centered development process that included workshops, intervention content development, and prototype testing. This study resulted in the creation of the Technology-Optimized Practice Process in Nursing (TOPP-N) guidance and assessment application for use as a supportive tool for nursing students, nurse preceptors, and nurse educators in clinical practice. The development process included the application's name and logo, technical architecture, guidance and assessment module, and security and privacy. This study offers insights into the development of an evidence-based technological tool to support nursing students, nurse preceptors, and nurse educators in clinical practice. Furthermore, the developed application has the potential to meet several challenges reported in nursing education in clinical practice. After a rigorous development process, we believe that the TOPP-N guidance and assessment application prototype is now ready to be tested in further intervention studies.

A Crossrate-Based Approach for Reliability-Based Multidisciplinary Dynamic System Design Optimization

In practical applications, the multidisciplinary dynamic system design optimization (MDSDO)-based solution is limited by uncertainty, which causes random variation in the physical design variable in the static discipline and the equation of state in the dynamic discipline. To address the lack of reliability of the MDSDO solution, a crossrate-based MDSDO approach (C-MDSDO), consisting of the MDSDO stage and a reliability assessment stage, is proposed in this paper. In the reliability assessment stage, a sub-optimization problem based on the crossrate of the objective reliability index sample trajectory is designed to obtain the shifting vector, which is employed to obtain a sufficiently reliable solution. In addition, the proposed approach adopts a sequential problem-solving framework that avoids nested optimization and a reliability assessment. One numerical case and two engineering cases were employed to validate the effectiveness of the proposed method. The results show that the reliability of the proposed solutions significantly improved.

The Effects of the Degree of Hybridisation on the Design of Hybrid-Electric Aircraft Considering the Balance between Energy Efficiency and Mass Penalty

The growing interest in the application of the hybrid-electric concept demands a rigorous method applied to balancing the energy efficiency improvement with the mass penalty. In hybrid-electric aircraft (HEA) design, it is necessary to avoid excessive usage of energy, which is caused by deliberate hybridising in pursuit of high electrical energy conversion efficiency. This paper presents a design method to achieve multi-objective designs conducted within a framework of multi-disciplinary design exploration appropriate for HEA, meeting the requirement of minimising the maximum take-off mass (MTOM) and fuel saving. A theoretical analysis proposes the existence of the optimum design area of HEA. This is followed by a series of demand-focused numerical design experiments that have verified the existence and position of the optimum design area by taking the mission of a short-range narrow-body airliner as the design target, considering the predicted technology timeline until 2050. Compared to a fuel-powered twin-turbofan aircraft, 65.56% fuel-saving, 16.4% reduction in flight operation cost, 44.58% reduction in block CO2 emission, and 75% improvement in the cost-specific air range (COSAR) are achieved via hybridisation using the proposed design optimisation method.

Integrating Nonlinear Controllability into a Multidisciplinary Design Process

Even in multidisciplinary aircraft design, most aspects of nonlinear controllability are only considered in later design phases. Hence, control considerations are not used to inform the overall design of the airframe. This paper presents a control-aware controller-agnostic design optimization framework that integrates nonlinear controllability constraints, which are informed by the solutions to optimal control problems, into the multidisciplinary design process. To implement the optimization, procedures to evaluate the sensitivity of the controllability constraint to variations in the design variables are defined. A supersonic aircraft case study illustrates the methodology and the steps involved in the process. The proposed approach enables the integration of control-related constraints into gradient-based design optimization.

System-Level Assessment of a Partially Distributed Hybrid Electric Propulsion System

Abstract Hybrid electric propulsion system-based aircraft designs are paving the path toward a future greener aviation sector and thus, have been the major focus of the aeronautical community. The fuel efficiency improvement associated to such propulsion system configurations are realized at the aircraft level. In order to assess such benefits, a radical shift in the subsystem modeling requirements and of a conceptual-level aircraft design environment are necessary. This work highlights performance model development work pertaining to different hybrid electric propulsion system components and the development of a design platform that facilitates tighter integration of different novel propulsion system disciplines at the aircraft level. Furthermore, a serial/parallel partially distributed hybrid electric propulsion system is chosen as the candidate configuration to assess the potential benefits and associated tradeoffs by conducting multidisciplinary design space exploration studies. It is established that the distributed hybrid electric configurations pose the potential for aircraft structural weight reduction benefits. The study further illustrates the impacts of onboard charging during the low thrust requirement segments, quantitatively. The provision of onboard charging lowers the potential for block fuel savings, and improvement in battery specific energy can make it more promising, which is also dependent on the hybridization power level. It is established that distributed propulsion system configurations particularly benefit from a high aspect ratio wing structure, which manifests in high hybridization power levels. A high voltage level transmission system with more efficient electrical components enhances opportunities for achieving block fuel saving benefits.

Design exploration and optimization of aerodynamics and radar cross section for a fighter aircraft

The design for the conflicting requirements of low drag and low Radar Cross Section (RCS) causes difficulty in achieving an aerodynamically superior stealth aircraft. To cater the issue, a multidisciplinary design exploration and optimization framework is proposed. A shared parameterized aircraft geometry is used for high fidelity aero-stealth analysis using Computational Fluid Dynamics (CFD) and Shooting and Bouncing Rays (SBR) techniques. A surrogate model using a machine learning approach involving Gaussian Process (GP) modelling is generated for efficient and rapid design space exploration. A gradient-free metaheuristic optimization scheme using multi-objective Genetic Algorithm (GA) is employed to minimize drag and RCS. The results show that the proposed framework provides a reliable environment for the multidisciplinary design exploration of an aerial vehicle.

Multi-disciplinary engineering design of a high-speed nature-inspired unmanned aquatic vehicle

Recently, small unmanned vehicles have increased their technological importance and practical relevance in private and public interest maritime applications. However, due to this technology's novelty and early stages, complex challenges in engineering design remain unsolved. Therefore, the purpose of this article is to demonstrate the development of an innovative high-speed Unmanned Aquatic Vehicle (UAV) with the inclusion of robust and multi-objective optimization-based methods. This work implemented four robust optimization methods (e.g., efficient low drag generation, theoretical calculation, the production of hydrodynamic forces, and fluid-structure interaction) to design, components, performance, and material optimization. Furthermore, robust computational simulations and mathematical modelling were applied during the engineering design process. The main research findings show that the version of the UAV developed is optimized and able to operate in several working conditions in oceanic applications. Findings also complement previous related studies and offer novel technological alternatives for maritime applications and species detection in complex oceanic conditions. Finally, the aspects of theoretical significance and application value of the research are discussed in the paper.

Investigation of antioxidant and antimicrobial activities of walnut (Juglans regia L.) kernel septum

Objectives: Walnut (Juglans regia L.) kernel septum (or septa) (WKS), a traditional nutraceutical material in China, has not been explored in detail. In this study, antimicrobial activity, total phenolic content (TPC) and antioxidant-oxidant status of WKS was investigated in case it may be clinically important in the management of various complications. Methods: The WKS was extracted with ethanol in a Soxhlet device. TPC of WKS was analysed by using Folin-Ciocalteu’s method. Antioxidant activity was obtained by using Rel Assay Diagnostics kits. The antimicrobial activity of WKS was evaluated against two Gram-positive (Staphylococcus aureus, Bacillus subtilis), one Gram-negative bacteria (Escherichia coli) and one fungus (Candida albicans) strains using the agar diffusion method. Results: The TPC of WKS was found to be 119.42 ± 2.39 mg GAE/gDW. It was determined that total antioxidant status (TAS), total oxidant status (TOS) and oxidative stress index (OSI) values were 7.542 ± 0.389 mmol/L, 3.718 ± 0.287 µmol/L and 0.049 ± 0.001, respectively. WKS selectively inhibited the growth of Gram-positive bacteria and fungus, while S. aureus was the most susceptible one with 16 mm of inhibition zone. Gram-negative bacteria was resistant to the extract. Conclusions: As far as we know, this paper is the first work that demonstrates the antioxidant-oxidant status of WKS by using the method described above, and moreover there are no scientific reports which have examined WKS in such a multidisciplinary experimental design. This study strongly supports the reported traditional use of WKS. Results indicated that WKS can be used as a pharmacological natural agent due to its high antioxidant and antimicrobial activities.