Software Capabilities Research Articles

PERFORMANCE INVESTIGATION OF A 5 MW PHOTOVOLTAIC SYSTEM: ALFASHIR SUDAN

This study comprehensively analyzes the operational performance and economic feasibility of a 5MW grid-connected photovoltaic in Sudan over a two-year monitoring period. Leveraging the capabilities of PVSyst software, the actual plant performance was rigorously compared to simulation predictions. Results revealed a significant disparity between observed and simulated energy generation, prompting the exploration of potential areas for enhancement. Seasonal fluctuations in the performance ratio were evident, with peak values during some seasons, albeit not consistently aligning with simulation projections. Despite these challenges, the Plant made a notable impact by reducing CO2 emissions, highlighting the environmental benefits of solar energy. Financial analysis unveiled discrepancies between actual and simulated savings, underscoring the need for optimization and efficiency improvements. The equity payback period, influenced by electricity pricing policies, was estimated at 15 years, emphasizing its role in assessing project economics. The region's high radiation intensity and humidity levels emerged as significant factors affecting plant performance. Addressing these challenges is crucial for maximizing the PV plant's operational efficiency and viability. Our Recommendations include thoroughly examining control system functions during commissioning and improving operational accuracy.

Predicting structural, elastic, and optoelectronic properties of oxide perovskites HfXO3 (X =Be, Mg) employing the DFT approach

This study conducts a comprehensive exploration of the structural, electronic, elastic, and optical properties of HfXO3 (X=Be, Mg) perovskite compounds, employing density functional theory (DFT) within the WIEN2k code. Employing the Birch Murnaghan fitting technique, our structural evaluation establishes the structural stability of these materials, with optimized lattice constants underscoring their stability at specific values. By harnessing the capabilities of the IRelast software, we have determined elastic constants and characterized the anisotropic tendencies, disclosing that both compounds exhibit a pronounced degree of anisotropy. Moreover, an in-depth investigation into electronic attributes, facilitated by the modified Becke–Johnson potential, uncovers these materials as indirect narrow band gap semiconductors, with calculated band gaps of 1.14 eV for HfBeO3 and 0.8 eV for HfMgO3 serving as vital indicators of their electronic character. Furthermore, we delve into the optical traits of these materials, revealing their photon transparency within the energy spectrum of 0 eV to 15 eV. These key optical properties encompass dielectric functions, refractive index, optical conductivity, absorption coefficient, extinction coefficient, energy loss function, and reflectivity. This comprehensive exploration offers a holistic understanding of the optical behaviors exhibited by these materials. By skillfully combining structural, electronic, elastic, and optical analyses, this study significantly contributes to the comprehension of HfXO3 (X=Be, Mg) perovskites, forging a path for their potential applications and serving as a foundation for future research endeavors.

Autonomous Robotic Capabilities in Space Exploration: From Mars to Beyond

The historical timeline of automated systems functioning in space settings spans around 75 years, whereas the existence of practical automated equipment to facilitate astronomical observation dates back over 200 years. Over time, physical servomechanisms have seen advancements in both hardware and software capabilities, enabling their successful operation on the Martian surface and even during journeys to the heliopause, which marks the outer boundary of interstellar space. Contemporary spaceflight operations exemplify a growing capacity to provide decentralized coordination across several automated systems, intricate communication networks, and diverse communities of scientists and engineers. This article examines the impact of autonomous robotic functionalities on space explorations, specifically emphasizing the investigation of Mars' surface. The article examines the use of robotic systems in past missions, specifically focusing on their application in activities like as the identification and analysis of water ice deposits, study of geological features, and the deployment of sensor devices. The article further emphasizes the achievements of autonomous operations in missions conducted in Earth's orbit, as well as the progress made in developing autonomy for operations in close vicinity to minor celestial bodies. This research explores the Chang'e 4 lunar mission and the OSIRIS-REx mission as instances of autonomous exploration and sample gathering on minor celestial bodies. The research also encompasses the exploration of prospective autonomy in forthcoming expeditions to oceanic realms and distant locales.

Russian young people's subjective health evaluations, self-care practices, and therapeutic networks.

This study investigates the relationship between young people's subjective health evaluations, self-care practices, and therapeutic networks using semi-structured interviews and the computerized qualitative thematic analysis capabilities of the MAXQDA software. In the summer of 2022, 41 Russian youths, ages 16 to 25, took part in this investigation. The major findings demonstrate that young people who had low health evaluations were more likely to conduct self-care with the intention of enhancing their health and to have mothers and other medical experts in their therapeutic networks. Furthermore, individuals who claimed that their health was inadequate engaged in more sports and took care of themselves even when they were ill. There was no association between the objectives of self-care practices, members of the therapeutic network, and self-care activities in terms of the type of health evaluation. Overall, it is possible to suggest that the practices and the structure of therapeutic networks are related to self-evaluated health, but quantitative study is needed to verify the causal relationship.

Modern software capabilities for shape optimization of shells

The article is devoted to the shape optimization of shell structures in Comsol Multiphysics using three gradient-based methods: IPOPT (Interior Point OPTimizer), SNOPT (Sparse Nonlinear OPTimizer) and MMA or GCMMA (the Method of Moving Asymptotes). Two types of complex shapes, such as right helicoid and developable helicoid are taken for the computational experiment. The task is to investigate the initial design and optimization process of two helicoids. To obtain a more accurate result and an interesting design solution, the calculation is carried out using three physics-controlled mesh sizes: extra coarse, fine and extra fine with varying values of special optimization settings, such as maximum displacement (dmax) and filter radius (Rmin). The results obtained using the three methods allow to conclude that the mesh element size and studied parameters dmax and Rmin have a significant impact on the final optimization result.

Integration of Artificial Intelligence into Metallography: Area-wide Analysis of Microstructural Components of a Jominy Sample

Abstract Analysing the microstructure is an essential part of quality control in many steel manufacturing and processing operations. In this work, a promising method for autonomous analysis of microstructures in low-alloy steels based on artificial intelligence image analysis is presented. This study focuses on the classification of different microstructure components in metallographic images of steel microstructures using a Deep Convolutional Neural Network (DCNN) model. Since the accuracy of the model strongly depends on the size of the data set, a data set consisting of two million optical microscopy images was created to ensure the presence of different microstructure components and their combinations for training the system. The Jominy test was performed to verify the accuracy and capability of the microstructure analysis software. The AI makes it possible to analyse large amounts of image data with high precision and at the same time with less effort than conventional methods of microstructure components analysis.

Developments and applications of the HYDRUS computer software packages since 2016

AbstractThe HYDRUS codes have become standard tools for addressing many soil, agricultural, environmental, and hydrological problems requiring the evaluation of various subsurface physical, chemical, and biological processes. There are now many thousands of HYDRUS users worldwide, with thousands of applications of the HYDRUS models appearing in the peer‐reviewed literature. In this manuscript, we provide an overview of the capabilities of the most recent Version 5 of HYDRUS, focusing primarily on features implemented since 2016. We briefly describe the standard HYDRUS model and its standard and nonstandard specialized add‐on modules that significantly expand the capabilities of the software packages. The standard add‐on modules include HPx, UNSATCHEM, Wetland, Furrow, PFAS, COSMIC, DPU, SLOPE Cube, and Particle Tracking. Recent developments of the HYDRUS Package for MODFLOW are also described, along with additional capabilities incorporated into the graphical user interface supporting HYDRUS. Also discussed are new or improved options to simulate the fate and transport of environmental isotopes, multi‐cropping systems, compensated root water uptake, and hydraulic redistribution within the rootzone, which will be implemented in upcoming add‐on modules. Another objective is to review selected applications of the HYDRUS models, such as evaluations of various irrigation, low‐impact development (LID), and managed aquifer recharge (MAR) schemes.

Total Knee Arthroplasty Kinematics Predict Patient-Reported Outcome Measures: Implications for Clinical Kinematic Examinations

BackgroundA core tenet of total knee arthroplasty (TKA) is that achieving more natural kinematics will lead to superior patient outcomes. Yet this relationship has not been proven for large representative cohorts of TKA patients because accurately measuring 3-dimensional TKA kinematics is time-consuming and expensive. But advanced imaging systems and machine learning–enhanced analysis software will soon make it practical to measure knee kinematics preoperatively and postoperatively in the clinic using radiographic methods. The purpose of this study was to assess the reported relationships between TKA kinematics and outcomes and distill those findings into a proposal for a clinically practical protocol for a clinical kinematic exam. MethodsThis study reviewed the recent literature relating TKA kinematics to patient outcomes. There were 10 studies that reported statistical associations between TKA kinematics and patient outcome scores utilizing a range of functional activities. We stratified these activities by the complexity of the radiographic examination to create a proposed examination protocol, and we generated a list of requirements and characteristics for a practical TKA clinical kinematic examination. ResultsGiven considerations for a clinically practical kinematic exam, including equipment, time and other resources, we propose 3 exam levels. With basic radiographs, we suggest studying single-leg stance in extension, lunge or squat, and kneeling. For fluoroscopic systems with X-ray pulses up to 20 ms, we propose chair-rise or stair ascent to provide additional dynamic information. For fluoroscopic systems with X-ray pulses of less than 10 ms, we propose rapid open-chain knee flexion-extension to simulate the highly dynamic swing phase of gait. ConclusionsIt is our hope that this proposed examination protocol spurs discussion and debate so that there can be a consensus approach to clinical examination of knee and TKA kinematics when the rapidly advancing hardware and software capabilities are in place to do so.

АКТУАЛЬНЫЕ ПРОБЛЕМЫ ВНЕДРЕНИЯ НОВЕЙШИХ ЦИФРОВЫХ ТЕХНОЛОГИЙ ДЛЯ ПОДГОТОВКИ СОТРУДНИКОВ ЭКСПЕРТНО-КРИМИНАЛИСТИЧЕСКИХ ПОДРАЗДЕЛЕНИЙ

Problems of using artificial intelligence as an effective means of software for activities of forensic experts in foreign countries and introduction of capabilities of new software for training specialists from law enforcement agencies in Russia are considered. Development prospects are outlined, as well as use of extensive capabilities of artificial intelligence in areas related to forensic activities.

Editorial: Special Issue on Opportunities and Challenges with Autonomous Racing

In the ever-evolving landscape of autonomous vehicles, competition and research of high-speed autonomous racing emerged as a captivating frontier, pushing the limits of perception, planning, and control. Autonomous racing presents a setup where the intersection of cutting-edge software and hardware development sparks unprecedented opportunities and confronts unique challenges. The motorsport axiom, “If everything seems under control, then you are not going fast enough,” resonates in this special issue, underscoring the demand for algorithms and hardware that can navigate at the cutting edge of control, traction, and agility. In pursuing autonomy at high speeds, the racing environment becomes a crucible, pushing autonomous vehicles to execute split-second decisions with high precision. Autonomous racing, we believe, offers a litmus test for the true capabilities of self-driving software. Just as racing has historically served as a proving ground for automotive technology, autonomous racing now presents itself as the crucible for testing self-driving algorithms. While routine driving situations dominate much of the autonomous vehicle operations, focusing on extreme situations and environments is crucial to support investigation into safety benefits. The urgency of advancing highspeed autonomy is palpable in burgeoning autonomous racing competitions like Formula Student Driverless, F1TENTH autonomous racing, Roborace, and the Indy Autonomous Challenge. These arenas provide a literal testbed for testing perception, planning, and control algorithms and symbolize the accelerating traction of autonomous racing as a proving ground for agile and safe autonomy. Our special issue focuses on cutting-edge research into software and hardware solutions for highspeed autonomous racing. We sought contributions from the robotics and autonomy communities that delve into the intricacies of head-to-head multi-agent racing: modeling vehicle dynamics at high speeds, developing advanced perception, planning, and control algorithms, as well as the demonstration of algorithms, in simulation and in real-world vehicles. While presenting recent developments for autonomous racing, we believe these special issue papers will also create an impact in the broader realm of autonomous vehicles.

An effective strategy for assembling the sex-limited chromosome.

Most currently available reference genomes lack the sequence map of sex-limited (such as Y and W) chromosomes, which results in incomplete assemblies that hinder further research on sex chromosomes. Recent advancements in long-read sequencing and population sequencing have provided the opportunity to assemble sex-limited chromosomes without the traditional complicated experimental efforts. We introduce the first computational method, Sorting long Reads of Y or other sex-limited chromosome (SRY), which achieves improved assembly results compared to flow sorting. Specifically, SRY outperforms in the heterochromatic region and demonstrates comparable performance in other regions. Furthermore, SRY enhances the capabilities of the hybrid assembly software, resulting in improved continuity and accuracy. Our method enables true complete genome assembly and facilitates downstream research of sex-limited chromosomes.

XXIII CPSYS Interdisciplinary Topics in Mining, Geology and Geomatics

13-15 JUNE 2023 | WROCLAW, POLAND HYBRID EVENT The title of the Conference XXIII Conference of PhD Students and Young Scientists “Interdisciplinary topics in mining, geology and geomatics” The location and the date of the conference hybrid event – online and onsite conference, 13th to 15th June, 2023 in Wroclaw, Poland XXIIIrd Conference of PhD Students and Young Scientists “Interdisciplinary topics in mining, geology and geomatics” continues a series of events that started in 2000 at Wroclaw University of Science and Technology. Scientific programme of the Conference focuses on four thematic panels:1. Mining Engineering: sustainable development, digitalisation in mining, problems of securing, protecting and using remnants of old mining works, underground mining, open-pit mining, mineral processing, waste management, mining machinery, mine transport, economics in mining, mining aeronautics, ventilation and air conditioning in mines2. Earth and Space Sciences: geology, hydrogeology, environmental protection, extraterrestrial resources, groundwater and medicinal waters, engineering and environmental protection, geotourism3. Geoengineering: environmental protection, applied geotechnics, rock and soil mechanics, geohazards4. Geoinformation: mining geodesy, GIS, photogrammetry and remote sensing, geodata modeling and analysis.The XXIII Conference of PhD Students and Young Scientists was held as a hybrid event, that is as a traditional onsite conference with the possibility in on-line participation in real-time.The XXIII Conference of PhD Students and Young Scientists took place in 13th to 15th June, 2023 in Wroclaw, Poland. Because the conference focused on four thematic panels, four different special opening lectures were delivered by wellknown scientists:- Professor Tim Wright (University of Leeds, England)- Professor Rubén Galindo-Aires (Technical University of Madrid, Spain)- Professor Przemysław B. Kowalczuk (Norwegian University of Science and Technology, Norway)- Dr. Jakub Ciążela (Polish Academy of Sciences, Poland).The Conference was divided into 7 oral sessions (with 29 presentations) and 1 poster session (with 40 posters). The amount of time provided to one presentation was 15 minutes, after presentation there was 5 minutes available for discussion. The poster session was available throughout the event, and the posters were available for online viewing on the Conference’s website with the possibility of make discussion and ask questions in real time via zoom meeting application as well.During this year’s Conference, Organizing Committee has prepared a unique opportunity to participate in onsite workshop. The aim of the workshop was to familiarize participants with the capabilities of ArcGIS Pro software in utilizing Deep Learning tools. They were learning how to create training samples, train models, and use them for their research.List of Scientific Committee, Organizing Committee Editorial Team are available in this Pdf.

Enhancing Energy Efficiency and Real-time Monitoring in Industrial Environments through an Integrated Software Solution: NIGHTWATCH

Globally, the demand for energy continues to escalate due to factors such as heating, lighting, transportation, and fuel supply for various devices. In a context where energy has garnered such paramount importance, achieving energy efficiency has necessitated a comprehensive approach encompassing activities related to energy generation, transmission, and consumption. Any positive or negative developments in the realm of energy significantly impact both human and environmental factors, which constitute the focal points of sustainable development. The presented study, operates within industrial settings and interfaces with energy analyzers, collecting and analyzing data such as energy consumption, instantaneous current, and voltage. This initiative seeks to provide real-time visibility into energy-related operations on factory premises. Additionally, the software's capabilities extend to retrospective data analysis, enabling informed insights for future extrapolations. Furthermore, the integration of energy consumption data from the analyzers into the Manufacturing Execution System (MES) facilitates energy tracking on a per-job basis. The software's dashboard component empowers users to establish customized threshold values for monitored energy parameters. When these thresholds are exceeded or when values deviate from expected levels, the software triggers alerts and notifications via email and other communication channels, ensuring timely dissemination of pertinent information. Consequently, the software allows businesses to evaluate unit costs associated with specific job orders. Additionally, the study aims to establish a correlation between energy consumption data at the job-order level and machine-level energy consumption. This correlation could foster the augmentation of efficient energy utilization, thereby enhancing competitiveness and overall efficacy.

Transforming Emergency Medical Services with Electric Ambulance Technology

Abstract: The focus of this project is to design and implement cutting-edge software features within the Electric Ambulance. These features are tailored to streamline the identification and availability of medical appliances and medications on board. The goal is to optimize the response time and ensure that paramedics have immediate access to the necessary tools for providing effective patient care. Complementing the software enhancements is the integration of a Laboratory System, driven by Lab-on-Chip (LOC) technology. This system is poised to revolutionize pre-hospital care by enabling on-the-spot health examinations, facilitating accurate first aid, and initiating prompt treatment. The marriage of advanced software and laboratory capabilities sets the stage for a new era in emergency medical services.

Topology optimization and numerical verification in an aircraft engine bracket

The importance of saving energy and materials by lightening structures is constantly increasing. With its powerful software capabilities, Topology Optimization produces solutions for this exact purpose. In addition, thanks to Topology Optimization, more innovative and competitive structures can be produced. The development of additive manufacturing methods has also increased interest in Topology Optimization. In Topology Optimization, volumetric elements that do not carry any load or carry little load are removed from the structure. Thus, lighter, but sufficiently durable structures can be obtained. In this study, the topology optimization of a bracket used as a fastener in a jet engine was carried out using ABAQUS Finite Element software. Required bracket geometry, load conditions, and material information were obtained from an online design competition announced by General Electric. Ti6Al4V alloy was used as the bracket material. At the beginning of the study, static analysis was performed on the original bracket model to obtain the load paths required for topology optimization. As a result of the static analysis, the load paths within the jet engine bracket were determined and topology optimization was applied to the bracket to minimize the mass without reducing the rigidity. As a result of the analysis studies, it has been proven that nearly 80% material savings can be achieved from the bracket thanks to topology optimization.

Perturbed Gerdjikov–Ivanov equation: Soliton solutions via Backlund transformation

The perturbed Gerdjikov–Ivanov (pGI) equation, a mathematical model that depicts the behaviour of optical pulses during propagation while accounting for perturbation influences, has been thoroughly studied by us. This equation has significant applications in the field of optical fibres, notably for photonic crystal fibres. In this paper, we combined the Riccati-Bernoulli sub-ODE method with the Backlund transformation to construct travelling wave solutions for the perturbed Gerdjikov–Ivanov (pGI) equation. This technique offered us families of solutions as well as a fresh way of dealing with nonlinear models. The results that emerge could greatly advance our knowledge of the physical consequences that are present in the nonlinear model that we are studying. The resulting solutions broaden the scope of earlier findings made using various approaches by including solitons, trigonometric functions, and rational expressions. The Backlund transformation used in this study is distinguished by its simplicity and brevity, and it produces results that are noticeably more thorough than those often obtained by alternative methods. Additionally, we create graphical representations of our results using the computational capabilities of the Maple software. In order to do this, the proper parameter values must be chosen, allowing for a visual study of the results. Through the display of two-dimensional graphical depictions, these effects have been clearly explained, permitting a thorough understanding of their physical implications.

Principles of Constructing a HIL Simulation Stand for Debugging Automated Process Control Systems based on the Baget PLC

The problem of constructing a HIL simulation stand for researching a technological process using programmable logic controller (PLC) "Baget" is described in this article. Issues of modeling technological processes are currently extremely relevant, since modeling is a mandatory stage in the automated process control systems development. An adequate model of the technological process allows debugging and verification of automated process control system algorithms without using real equipment, reducing financial costs and the probability of emergency situations. The HIL modeling method involves partial use of real equipment as part of the model. The inclusion of standard components of the original object in the model does not require detailed mathematical model and at the same time provides a more complete correspondence to the original. Due to using a computer from the original object, the stand software operates under conditions close to the real technological process, which improves the quality of the simulation results. The HIL modeling stand includes the following components: control computer of automated process control system; programmable logic controller PLC "Baget"; simulation computer. The stand for the basic element of an automated process control system allows to speed up the process of prototyping and debugging even in the case of complex systems, because it will be easier to build the entire system from correctly functioning elements. Another advantage of this approach is that the stand is not tied to a specific type of technological process or to a narrow area of production — the stand allows the use of ready-made models, the development of new models, and the inclusion of various function libraries. The simplicity of the stand design with this approach is combined with a full range of functionality. By connecting additional software, you can create more complicated and detaild model. This stand is also capable of serving both for debugging PLC algorithms and as a simulator for maintenance personnel of a real control object, because the stand operator can simulate failures and errors of standard equipment, emergency situations at the control object. Using C and JavaScript programming languages for development ensures portability and ease of expanding the capabilities of the modeling software. The development of complex systems based on HIL modeling allows saving resources and effectively solving assigned problems, therefore the proposed approach to building stands will be in demand in the process of developing an automated process control system based on the PLC "Baget".

The Impact of Instagram's Corporate Strategy on Consumer Preferences

Instagram's enterprise strategy has had a significant impact on consumer preferences, particularly in terms of its software capabilities, content delivery, and seamless integration of music. These elements shape the user experience and influence how users interact with the platform. Brands can leverage these characteristics to build stronger connections with their target audiences and create more targeted content that resonates with customers. Instagram's ability to deliver highly targeted ads based on user interests and demographics further enhances its impact on consumer preferences, increasing brand awareness and driving sales. The platform's emphasis on visual and user-generated content has also changed how consumers perceive and engage with brands, emphasizing the importance of authenticity and relevance. Additionally, Instagram's integration with other social media platforms expands its reach and influence, allowing for a cohesive online presence across multiple platforms. However, caution should be exercised when selecting internet celebrities for campaigns due to the prevalence of fake accounts and inflated data. The success of Instagram lies in its fusion of content distribution and interpersonal relationships, providing a unique social networking experience that goes beyond a mere photo-centric service.

Preliminary cost forecasting and optimization for the construction of steel pedestrian bridges in Egypt

PurposeThis research aims to create a methodology that integrates optimization techniques into preliminary cost estimates and predicts the impacts of design alternatives of steel pedestrian bridges (SPBs). The cost estimation process uses two main parameters, but the main goal is to create a cost estimation model.Design/methodology/approachThis study explores a flexible model design that uses computing capabilities for decision-making. Using cost optimization techniques, the model can select an optimal pedestrian bridge system based on multiple criteria that may change independently. This research focuses on four types of SPB systems prevalent in Egypt and worldwide. The study also suggests developing a computerized cost and weight optimization model that enables decision-makers to select the optimal system for SPBs in keeping up with the criteria established for that system.FindingsIn this paper, the authors developed an optimization model for cost estimates of SPBs. The model considers two main parameters: weight and cost. The main contribution of this study based on a parametric study is to propose an approach that enables structural engineers and designers to select the optimum system for SPBs.Practical implicationsThe implications of this research from a practical perspective are that the study outlines a feasible approach to develop a computerized model that utilizes the capabilities of computing for quick cost optimization that enables decision-makers to select the optimal system for four common SPBs based on multiple criteria that may change independently and in concert with cost optimization during the preliminary design stage.Social implicationsThe model can choose an optimal system for SPBs based on multiple criteria that may change independently and in concert with cost optimization. The resulting optimization model can forecast the optimum cost of the SPBs for different structural spans and road spans based on local unit costs of materials cost of steel structures, fabrication, erection and painting works.Originality/valueThe authors developed a computerized model that uses spreadsheet software's capabilities for cost optimization, enabling decision-makers to select the optimal system for SPBs meeting the criteria established for such a system. Based on structural characteristics and material unit costs, this study shows that using the optimization model for estimating the total direct cost of SPB systems, the project cost can be accurately predicted based on the conceptual design status, and positive prediction outcomes are achieved.

Precision of grain yield monitors for use in on-farm research strip trials

On-farm research (OFR) has become popular as a result of precision agriculture technology simplifying the process and farm software capabilities to summarize results collected through the technology. Different OFR designs exists with strip-trials being a simple approach to evaluate different treatments. Common in OFR is the use of yield monitors to collect crop performance data since yield represents a primary response variable in these type studies. The objective was to investigate the ability of grain yield monitoring technologies to accurately inform strip trials when frequent yield variability exists within an experimental unit. A combination of six sub-plot treatment resolutions (TR) that differed in length of imposed yield variation (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were harvested at combine ground speeds of 3.2, 6.4, 7.2, and 8.1 kph, depending on study site (three study sites total). Intentional yield differences in maize (Zea mays L.) were created for each sub-plot by alternating the amount nitrogen (N) applied: 0 or 202 kg N/ha. Yield was measured by four commercially available yield monitoring (YM) technologies and a weigh wagon. Comparisons were made between the accumulated mass of the YM technology and weigh wagon through percent differences along with testing the significance of the plotted relationship between YM and weigh wagon. Results indicated that yield monitoring technology can be used to evaluate strip trial performance regardless of yield frequency and variability (error < 3%) within an experimental unit when operating within the calibrated range of the mass flow sensor. Operating outside of the calibrated range of the mass flow sensor resulted in > 15% error in estimating accumulated weight and overestimation of yield by 23%. Finally, no significant differences existed in estimating accumulated weight values between grain yield monitor technologies (all p-values ≥ 0.54).