Design Stage Research Articles

Investigation of the effect of elbow pipes of Ti6Al4V, 304 stainless steel, AZ91 materials on erosion corrosion by finite element analysis

Corrosion is the degradation of metals caused by chemical or electrochemical reactions with their environment. As a result of these reactions, undesirable conditions occur in the physical, chemical, mechanical and electrical properties of metals. These conditions cause parts made of metallic materials to become unusable. Erosion corrosion is one of the most common types of corrosion in fluid transfer. There are several methods for preventing erosion corrosion. First of all, some precautions should be taken to prevent wear. Intervention is very important in terms of cost, especially at the design stage. Measures such as wide angle bends, wall thickness of wear-resistant material and corrosion allowance can be taken, especially in applications where the flow direction needs to be changed. The aim of this study was to determine the effect of liquid fluid on erosion corrosion in Ti6Al4V, 304 stainless steel and MgAz91 elbow pipes by using the computer aided and finite element based AnsysWorkbench Explicit Dynamics module. For the design of the elbow pipe, SolidWorks was used for 3D studies. In the analysis of the pipe, the suitability of the pipe for the 3D model was examined. The effect of fluid rotation on the pipe walls and the effect of the pipe material on the flow along the pipe were determined. The standard k-e model based on the velocity-pressure relationship in continuous and steady flow was used for the flow calculations. The flow simulation showed that for all models the flow accumulation after rotation was more concentrated on the opposite walls of the pipe, as expected. The results obtained showed that the deformation in MgAZ91 material had the highest value at 9.14 × 10−8 mm. This situation has been interpreted to mean that it may vary depending on the flow rate automation. Designs on the old designs in the erosion structure of the liquid that occurs in the pipes with a new product design in the analysis design.

Safety-driven design of carbon capture utilization and storage (CCUS) supply chains: A multi-objective optimization approach

Carbon capture, utilization, and storage supply chains (CCUS) play a pivotal role in achieving sustainability targets but necessitate meticulous risk identification and mitigation measures. Traditional safety assessments often occur post-design, constraining proactive risk management efforts. Hence, there is a pressing need to optimize safety performance during the design stages. To address this challenge, a framework for evaluating and optimizing CCUS supply chain safety performance using inherent safety index system (ISI) is introduced. Recognizing the trade-offs between total cost, environmental impact reduction, and risk mitigation, our approach considers multi-objective optimization to concurrently address these sustainability objectives and generate a Pareto set of solutions. Utilizing the augmented ε-constraint method, we applied this framework to optimize CCUS networks and develop sustainable designs across three key objectives. The method was applied to a CCUS system that includes various CO2 utilization pathways to minimize the total annual cost, CO2 emissions, and safety risks. The resulting Pareto surface illustrates unique network configurations, each representing a distinct trade-off scenario. Through a case study, we optimized a CCUS network to achieve economic, environmental, and safety objectives. The most economically viable design, with a total annual cost of $97 million and a 40 % net carbon reduction, prioritizes CO2 utilization for value-added products, while limiting CO2 sequestration. Conversely, safety-focused designs shift utilization towards safer routes, including CO2 sequestration and algae production. The proposed framework offers a systematic approach to developing sustainable CCUS supply chain designs, balancing economic viability, environmental sustainability, and safety.

Impact of Spatial Layout Design on Energy Consumption of Ice Rinks in Cold Regions

The differentiated physical environment requirements within the internal space of ice rinks in cold regions result in a complex heat exchange process, which becomes the primary cause of high energy consumption. Therefore, analyzing the impact mechanisms of spatial layout parameters on the energy consumption of ice rinks is crucial during the early design stages. This study employed the Delphi method to identify the key parameters affecting the total energy consumption of ice rinks. It conducted single-factor experiments using building performance simulations to quantify the relationship between each layout parameter and the energy consumption. Based on the single-factor experiment results, orthogonal experiments were conducted to develop an energy-efficient spatial layout combination. The study indicates that the height-to-width ratio and the mixed area width are the most significant parameters. By adjusting the values of these parameters, the total energy consumption can be reduced by approximately 18% to 31%. The spatial layout strategy for ice rinks in cold regions proposed in this study will help architects make more effective decisions during the early design stages.

Design and Modeling of a Long Range Motion Compliant Nanopositioning Stage Driven by a Normal Stressed Electromagnetic Actuator

Compliant nanopositioning stages with built-in ultra-precision actuators are frequently integrated into production and analysis instruments comprising ultra-high precision motion generation systems. These stages are essential nanotechnology and advanced material analysis components, providing precise positioning capabilities for various applications. However, in the practical engineering field, there is a lack of compliant nanopositioning stages that can achieve a long-range motion while maintaining accuracy, reliability, and compact size, which is the inspiration for this research. This paper investigates the design, modeling, and experimental testing of a long-range motion-compliant nanopositioning stage driven by a normal stressed electromagnetic actuator (NSEA). The nanopositioning stage components’ structural framework and working principle, including NSEA, bridge type distributed compliant (BTDC) mechanism, and the guiding mechanism, are fully examined to derive an analytical model. The analytical model is utilized in the sections that follow. Factors affecting the stroke and natural frequency of the nanopositioning stage are also illustrated. The optimization process of the nanopositioning stage is conducted in pursuit of a high-precision stage by specifically looking into the electromagnetic, BTDC mechanism, and guiding mechanism parameters. This optimization procedure also takes into account various design constraints, including stiffness, saturation flux density, and stress. Furthermore, the finite element analysis is used to verify the analytical model, and the results are discussed. The prototype is fabricated with reference to the analytical and finite element analysis results, and the experimental tests are conducted, including motion and natural frequency tests. In addition, a control system, which adopts both a proportional-integral-derivative controller and a damping controller, is designed to create a closed-loop system. Finally, the tracking performance of the stage was investigated, and a very minimal tracking error was observed. Overall, the comprehensive models and experimental tests proved the stage to be a good model which achieved the objective of the research.

Predicting maximum deflection of N-Edged thin-shelled hyperbolic-Paraboloid umbrella using machine learning techniques

Many thin-shelled hyperbolic paraboloid (hypar) umbrella forms have been built in the last 60 years as roof coverings. While the stresses in these forms remain relatively low, the deflections are a critical design parameter, and one that must be considered by architects and engineers in the conceptual design phase, meaning the design stage when the scale and form is given to the structure. To-date, there is no closed-form solution that can predict the maximum deflection of umbrellas due to their highly varying and complex geometry. The best option for predicting deflection is via finite element analysis, which is time-consuming for conceptual (preliminary) design purposes. In response, this paper uses machine learning via genetic programming (GP) and gene expression programming (GEP) to develop closed-form equations that predict the maximum corner deflection of N-edged hypar umbrellas – where N = 3, 4, 5, 6, 7, and 8. For a given a boundary condition and material, geometry is the most significant parameter influencing a shell's stiffness; thus, elastic finite element (FE) models use geometric properties as input variables (N, projected area, normalized rise, and shell thickness). The maximum corner deflection is recorded as an output and the FE analyses generate a large dataset of 53,754 results. It is observed that both GP and GEP can effectively parameterize the maximum deflection of N-edged hypar umbrellas, with GEP producing more concise, but relatively less accurate, equations than GP. While the formulations are trained using concrete material, a material factor multiplier transforms the results to other material properties within the assumption of elastic limits. The results of the study can be used to assist with conceptual design of hypar umbrellas and to validate complex FE models of hypar umbrellas. This research also illustrates the use of machine learning techniques as applied to the conceptual design of structures with highly varying geometries.

Increasing R&D effectiveness: planning as a tool for reducing technological risk in engine development

This article presents the basics and results of applying the Lean R&D methodology in planning as a crucial tool for enhancing the success of innovative projects. By following a step-by-step process, the effectiveness of project execution is improved through a comprehensive list of key tests that increase in complexity. This approach simplifies early identification of potential issues and reduces the risk of errors during the design phase. A new lean planning method is introduced, including assessing the readiness of the designed product at the design stage based on a roadmap. It also involves analyzing the critical elements (CE) of the product and determining their current level of readiness. Additionally, a functional analysis of the CE is conducted, followed by separate planning for the development of each element. Finally, the project is checked against a set of criteria to achieve technology readiness levels (TRL+). The process of lean planning is demonstrated in the field of engine building through the case of integrated starter-generator (SG) development. Specific elements of the planning structure are considered, and a functional analysis of the SG’s CE is conducted for both internal and external primary and secondary impacts. Their interactions and control events are determined according to detailed TRL+ criteria, allowing for the reduction of technological risks, shorter project execution times, and increased efficiency in innovative technology development through the use of this planning tool

Implementation of Ideological and Political Theory Course Based on Problem-Based Learning Combined with Small Private Online Course teaching model to Enhance Learning Achievement and Citizenship of Chinese College Students

Background and Aim: Problem-based learning is a kind of targeted and practical learning for students to solve real problems. In the problem design stage, the design of problem scenarios is the core of problem-based learning. The concept of Small Private Online Course (SPOC) was first proposed by Professor Armando Fox, director of MOOC Lab at the University of California, Berkeley, and is abbreviated for Small Private Online Course. In this study, Problem-Based Learning combined with a Small Private Online teaching model were combined to generate a new teaching model. This teaching model emphasizes the role of the problem in the teaching process. Learning throughout the course is an open and dynamic system that can be adapted and improved based on feedback. The purpose of this study was; 1) To compare students’ learning achievement before and after learning through ideological moral and legal basic courses based on problem-based learning combined with the Small Private Online Course (SPOC) teaching model and 2) To compare citizenship of Chinese college students before and after learning through ideological and political theory course based on problem-based learning and Small Private Online Course (SPOC) teaching model. Materials and methods: In this experimental study, 50 students (one class) from Xi’an University were investigated. This study used test and self-evaluation forms given to students before and after learning through ideological and political theory education based on problem-based learning combined with small private online (SPOC). Data were collected and analyzed by means, standard deviation, and dependent sample t-test. Results: The results of the learning achievement before and after learning based on problem-based learning and small private online (SPOC) on ideological and political theory course, it was found that the mean scores of pretests of students’ learning achievement were 13.31(SD=6.860) and mean scores of posttests were 17.32 (SD=7.197). The post-test score of students' learning achievement was higher than that of the pre-test score at.01 level of significance. Moreover, the results of citizenship of Chinese college students found that the mean scores of pretests of citizen self-evaluation scores were 35.42 (SD=9.338) and the mean scores of posttests were 44.18 (SD=9.736). The posttest scores of citizenships of Chinese college students were higher than that of the pretest scores at.01 level of significance. Conclusion: The developed ideological and political theory course based on problem-based learning combined with small private online (SPOC) has a significant effect on improving the learning achievement and citizenship of Chinese college students.

THE PROBLEMAIICS OF ENSURING THE RELIABILITY OF THE SIDE SURFACE OF THE PISTONS OF BOOSTED ICES

Prospective directions and trends in the development of special-purpose engines are analyzed. An increase in swept volume power density of engines leads to a critical raise in thermal and mechanical stress in the engine structural elements and to a corresponding reduction in its resource. Pistons are among the elements of boosted engines that are most prone to failure. Among the characteristic critical zones of the piston design, in which losses of parametric and physical reliability were observed, a separate critical zone on the loaded and unloaded side of the piston skirt near the piston pin bores is singled out. An analysis of publications was carried out and it was shown that the occurrence of the phenomenon of wear or seizures of the side surface of the piston skirt, which is observed for the boosted designs in the specified zone, is not explained exhaustively in the existing system of scientific views. Understanding the causes of the described phenomenon of loss of reliability is necessary for diagnosing and developing measures to prevent it at the design stage. The paper puts forward a hypothesis that explains the occurrence or non-occurrence of the loss of reliability in the process of deformation of the local zone of the side surface of the piston skirt during uneven expansion of the material in presence of creep and simultaneous stress relaxation with possible strengthening of the material by the property of creep limit. The possible cases of deformation of a certain local zone of the side surface of the piston in an elastic setting and in the presence of creep and stress relaxation processes are considered. It is shown that the process of creep deformation in the studied zone can end before the occurrence of reliability loss even for the materials that are unable to be strengthened by the property of creep limit or could be strengthened only insignificantly. The general ways of increasing the reliability of the side surface of the piston are outlined, related to ensuring the level of local stresses being below the creep limit, ensuring the completion of the creep process before the clearance reaches the critical values, as well as achieving strengthening of the material by the property of creep limit, for materials capable of it, before the occurrence of creep in operation.

The Use of Computational Modeling and Simulation to Design and Evaluate a Distributed Work System

Designing integrated systems of humans and automation involves envisioning how work will be performed, how it is affected by technological capabilities, and what will be helpful to support system performance. This is challenging as interactions and dynamics can create emergent effects that are difficult to predict. This demonstration aims to demonstrate the power of computational simulation in designing, verifying, and validating integrated systems of humans and automation. The demo will include an introduction to the simulation framework Work Models that Compute (WMC) used for our ongoing research, how to develop a work model in WMC, a demo of the simulation, and a demo of postprocessing visualization to analyze the simulation results. The approach can be applied in all stages of system design. With an example in aviation, we show how we use computational modeling and simulation to evaluate the robustness of envisioned operations of humans working with automated systems.

Analisis Kualitas Instrumen Penilaian Berbasis Kelas untuk Mengukur Kompetensi Literasi Sains Peserta Didik SMA pada Materi Energi Terbarukan

The aim of this research is to analyze the quality of class-based instruments in the domains of knowledge, attitudes and skills to measure scientific literacy competency. This research uses a limited ADDIE research design consisting of Analyze, Design and Development stages. Data was collected using test and questionnaire methods. This research was tested on 30 Unesa Physics Education Study Program students. Theoretical validity results show that the assessment instrument prepared meets the valid category. The theoretical validity results were obtained from validation by 3 expert validators, namely 2 Unesa Physics Education lecturers and 1 MBI Amanatul Ummah Pacet Mojokerto teacher. Empirical validity was obtained from testing the assessment instrument on 30 active Unesa Physics Education students with a total of 15 questions. Then, the question item was declared valid with an rcount of 0.922 and an rtable of 0.361.

Development of an Internet of Things-based Environmental Information System for Realtime Monitoring of Air Conditions

This study aims to develop an environmental information system called the Environmental Monitoring System (EENNOS) to monitor air environmental conditions. ENNOS is an Internet of Things (IoT) based system that monitors air environmental conditions in the form of temperature, humidity and carbon dioxide. The research was conducted using the 4D development method which consisted of the Define, Design, Develop, and Disseminate stages. EENNOS was developed using a DHT 22 sensor for DHT 22 temperature and humidity and a carbon dioxide sensor with MQ-135. The controller used is Arduino uno ESP8266 with output sending using the internet to the database and presented on the dashboard and displayed on a 16x2 liquid crystal screen. The output is in the form of dashboard innovations that are registered with copyrights and scientific publications in the form of articles in the Journal of Environmental Sciences.

A Hybrid Prototype Method Combining Physical Models and Generative Artificial Intelligence to Support Creativity in Conceptual Design

Conceptual design is an essential stage in the design process, and its ultimate success largely depends on designers’ creativity. Both physical and digital prototypes are commonly adopted by designers to support ideation and creativity, providing intuitive perception and rapid iteration, respectively. In recent advancements, large-scale generation models are able to offer data-enabled creativity support by generating high-quality solutions comparable to human designers. This opens up an imaginary space for designers and brings new possibilities for design tools. In this study, we proposed a hybrid prototype method that synergistically combines physical models and generative artificial intelligence (AI) in the conceptual design stage. Correspondingly, we developed a hybrid prototype system to implement the proposed method. We conducted a comparative user study with 45 designers who completed a design task using the physical prototype method, standalone generative AI, and the hybrid prototype method, respectively. Our results verified the effectiveness of the hybrid prototype method and investigated its mechanism in supporting creativity. Finally, we discussed the application value and optimisation space of the hybrid prototype method.

Bridging the gap in patent assessment: The Index of Internal Effort framework for pharma innovations

Context: The process of assessing patents is complex, and there is a gap in the literature on patent assessment at the time of filing. Aims: To assess patent complexity and the human effort involved in research, we test the effectiveness of the Index of Internal Effort (IIE) framework using pharmaceutical patents developed within the Brazilian public sector as a proof of concept. Methods: Internal data were collected from innovation projects that included the filing of patents as a project outcome. The Spearman correlation test was applied to determine which internal patent variables could be used as metrics in IIE. Then, IIE was used to measure the complexity of the patents and the individual effort of inventors. Results were then compared with other metrics identified in the literature. Results: The IIE showed a positive and significant correlation with resources invested at the design stage, as well as commercial and social outcomes of the patents. Conclusions: The results indicate that the generic IIE framework is a new form of metrification that can be applied to pharmaceutical patents that have not been previously discussed in the literature.

Installation of a Pit Fence in Cramped Conditions

The construction of buildings and structures in cramped conditions requires a special approach from hydraulic engineers and builders, requiring the preservation of the surrounding development in a working condition. This circumstance requires a geotechnical forecast of deformations of objects falling into the zone of geotechnical influence of the construction of a building under construction at the design stage and then the organization and implementation of geotechnical monitoring of deformations as a result of construction and installation work. It should be noted that the objects of the surrounding development can be in different categories of technical condition. According this circumstance the permissible deformations may be different. In any geotechnical case, there is an urgent need to install excavation fences that perform a dual task: both ensuring the stability of the soil walls, and reducing the impact of the new construction object on existing buildings. The determination of the bearing capacity of the enclosing structures of the excavation, especially the retaining soil anchors themselves, is of great importance in modern geotechnical construction. The engineering method used in this article to determine the bearing capacity of drilling-injection anchors with sufficient accuracy for technical calculations showed the convergence of calculated and real values based on the results of static tests.

NPFormer: Interpretable rotating machinery fault diagnosis architecture design under heavy noise operating scenarios

While existing models have achieved significant progress on fault diagnosis tasks, what interpretable temporal dependencies they capture to resist noise remains unclear. Previous studies have ignored the inherent non-stationary property of fault data, which is the basis for capturing reliable temporal dependencies under heavy noise operating scenarios. To tackle the aforementioned problems, we propose a non-stationary perception network (NPFormer). Firstly, we revisit the large kernel design in the early stage of the network, and we demonstrate that this can make the attention map more stable for modeling non-stationary series, which can be a more powerful paradigm with heavy noise interference. Secondly, an adaptive non-stationarity embedding block is developed, which breaks the raw data into multiple components and adaptively attenuates the non-stationarity of mechanical signals for better predictability. Finally, we design multi-scale fusion attention to capture fine-grained features with the global scope, while achieving localized spatial–temporal correlations. Extensive experiments have been conducted on three public datasets and the practical aero-engine engineering application, showing that NPFormer significantly outperforms existing state-of-the-art methods. The weight information is visualized to reveal how NPFormer works, which can demonstrate that the stable attention map is a clear clue of anti-noise. We quantitatively reveal the effect of noise on the model, and the model’s anti-noise clues, during model inference. Code and models will be available for further study.

Conducting mixed methods research with women in a forensic mental health setting: A reflexive account from a nurse as researcher.

To describe a reflexive account of a mental health nurse as researcher undertaking a mixed methods study as part of a doctoral degree, with women in a secure forensic hospital. A discursive paper that draws upon the primary author's experience of dual roles as a mental health nurse and a novice researcher, and relevant literature pertaining to positionality and reflexivity in the context of conducting mixed methods research. A mixed methods study was conducted within a secure forensic hospital in Australia, to identify factors associated with the frequency and duration of seclusion for women and, to explore their experiences of seclusion. Notes and a reflective diary were used to demonstrate the reflexive approach and strategies used throughout the study design and data collection stages of the research. Women in the secure forensic hospital setting often have complex histories and experiences and are considered a vulnerable group, which can add additional challenges when undertaking research with this population. As a doctoral student with clinical experience in mental health undertaking research in the forensic hospital setting with women, positionality and the connection with reflexivity requires exploration to understand self and the influence on research. This understanding along with identified strategies to enhance reflexivity, supports the management of the dual nurse as researcher roles to enhance all stages of the research process. Doctoral nursing candidates undertaking clinical research in their area of clinical practice and at the location of previous employment, may experience challenges in relation to identity and the dichotomy of roles. Further challenges can be posed when research involves complex populations and/or controversial practices. Support to balance role conflict and maintain reflexivity is critical to understanding the role of self in research and to enhance credibility. Women are a complex, yet minority population in forensic mental health settings, however the numbers of women being admitted to services is increasing. Future research may consider the use of the strategies explored here to enhance the reflexive process, and support future researchers in this field to conduct research that aims to support an often-misheard population to better support health outcomes. There was no patient or public contribution to this paper, however the study in which this paper is based on, is grounded in the experience of patients (women).

Design and modeling of PV-integrated Double Skin Facades and application to retrofit buildings

Double Skin Façade (DSF) system comprises two glazing layers with a ventilated cavity. Integrating photovoltaic (PV) modules within the outer layer of DSFs offers an efficient method for electricity generation. Current tools for modeling and analyzing DSF systems are complex and resource-intensive, lacking the capability to evaluate the performance of innovative PV-DSF systems during the early design stage. This study develops a mathematical model to evaluate the electrical and thermal performance of PV-DSF systems, considering architectural design elements such as PV color and relative orientation. Based on an energy balance approach, the model is particularly suited for designing PV-DSF systems in heritage buildings, which often have color and relative orientation constraints. The model is applied to assess the performance of PV-DSF systems with conventional clear glass PV and colored front glass PV modules under the climatic conditions of Montreal, Canada. Results indicated that conventional clear glass PV module exhibit higher PV cell temperature than colored PV modules due to greater transmissivity, with peak temperature differences at noon of 5.5 °C, 6.2 °C, and 6.5 °C for orange, blue, and gray PV modules, respectively. On the contrary, the influence of PV's color front glass on room air temperature is non-significant. Furthermore, the optimal orientation for maximum energy yield is not always south-facing; it depends on the hourly distribution of the beam, diffuse solar irradiation, and ambient air temperature. For Montreal, west-facing DSFs produce more electrical and thermal energy on a summer design day because the hourly distribution of beam radiation is skewed towards afternoon hours.

Optimal design of building envelope towards life cycle performance: Impact of considering dynamic grid emission factors

Building-related carbon emissions in the construction and operation stages account for more than one-third of global energy-related emissions. Optimizing during the early design stage is an effective way to reduce building carbon emissions. However, current studies adopt a constant grid emission factor (GEF) to assess the environmental impacts of buildings while ignoring the dynamic changes of the future electricity mix. This will overestimate the operational carbon emissions of the building in the context of the increasing share of renewable energy in power generation. In this study, a dynamic life cycle assessment model based on dynamic GEF is constructed to evaluate the life cycle environmental impacts of buildings. On this basis, a building optimization design framework considering dynamic GEF is proposed, and the impact of considering future variations of GEF on the optimal design of the building envelope is explored. The study is conducted in three steps. First, dynamically changing GEFs are predicted under the future electricity mix based on scenario analysis. Second, a multi-objective optimization framework is established to minimize the life cycle carbon emissions (LCCE) of the building while optimizing its life cycle costs (LCC) and indoor discomfort hours (IDH). Finally, the proposed optimization framework is applied to a prototype office building in Shanghai, and a comparative analysis is conducted for the optimal schemes between a static and two dynamic scenarios. The result reveals that ignoring future variations will lead to overestimating the operational carbon emissions by 49.0%-64.8%, which in turn will result in an over-insulated design of the envelope (i.e., additional material consumption). In addition, compared to the static scenario, consideration of dynamic GEF results in a 38.7%-51.6% reduction in LCCE, a 5.2%-6.1% reduction in LCC, and a 5.3%-9.5% increase in IDH for the optimal solutions. This research illustrates the importance of considering dynamic GEF in identifying the optimal design parameters and can help decision-makers reasonably choose the optimal schemes during early-stage design.

Influence of partition layouts on speech privacy in open-plan offices

Different partition layouts were compared to determine how to increase speech privacy while maintaining communication efficiency between workers in an open-plan office. A preliminary survey was used to determine current usage and conditions of partitions in open-plan offices. The survey results were used to select four partition layouts for testing: face-to-face, parallel, crossed-rod, and orthogonal. A computer modeling was used to test the partition layouts at three different partition heights: 1.2, 1.5, and 1.8 m. The modeling results showed that the parallel- and crossed-rod-type layouts offered the best speech privacy at the lowest partition height, but the differences among layouts disappeared as the partition height was increased. Furthermore, an acoustic field experiment was performed using partitions with a 1.5 m height following the ISO 3382-3 standard. The experimental results showed that the face-to-face layout resulted in the least speech privacy. Based on these results, an open-plan office needs to ensure that workers are spaced a sufficient distance apart and that they do not face each other to ensure speech privacy. Additionally, speech privacy should be considered in the design stage of the office space.

A highly survivable X‐band low noise amplifier based on GaN HEMT technology and impact of pulse width on recovery time

AbstractGaN high electron mobility transistor (HEMT)‐based low noise amplifiers (LNAs) are an integral part of microwave receiver systems to enhance signal‐to‐noise ratio (SNR). The noise of LNA itself becomes critical for systems requiring high SNR, such as imaging and satellite communication systems. This paper discusses the design of a three‐stage LNA operating at the X‐band in the frequency range of 8.0–12.0 GHz. The amplifier's design and small signal, noise, and linearity characterizations are discussed. Stagewise analysis for gain, noise figure (NF), and matching network losses at the design stage results in achieving promising results. The proposed LNA provides a gain of 23.2 dB with dB gain ripple. Its NF is below 1.5 dB, output power at 1 dB gain compression is 16.4 dBm, and third‐order intercept point is 24.7 dBm at 10 GHz. LNA's survivability is validated to input stress as high as 42 dBm. This LNA is the best reported NF and survivability combination in the 8.0–12.0‐GHz frequency range. The reverse recovery time of LNA is measured under two different pulse conditions, and it has been shown that LNA has better recovery times for lower pulse width signals. This LNA finds its applications in radars and satellite communication systems.