Engineering Commons^™

A Hands-On Lab On Agentic Scientific Discovery For Time Series With The Model Context Protocol, Dhaval Patel, Miaomiao Feng, Chathurangi Shyalika, Shuxin Lin, Hasnat Md. Abdullah

Publications

Agentic AI offers new opportunities to accelerate scientific discovery for time series by enabling autonomous systems to inspect data, formulate hypotheses, compose experiments, and refine models based on empirical evidence. However, building agents that make sound modeling decisions requires more than connecting a language model to forecasting tools. Key challenges include exposing large model catalogues without overwhelming the agent, grounding parameter choices in data characteristics, supporting iterative experimentation, and evaluating the quality of the reasoning behind each decision.

This hands-on lab introduces participants to agentic scientific discovery for time series using the Model Context Protocol (MCP). Through five interactive sprints, …

Thermal Modelling And Numerical Simulation Of Nanofluid-Based Battery Thermal Management System Using Lattice Boltzmann Method Under High Discharge Rate, Bahram Mahjoobkarambasti, Barun K. Das, Hussein A. Mohammed, Iftekhar Ahmad

Research outputs 2022 to 2026

Effective battery thermal management systems (BTMS) are essential to ensure performance, safety, and lifetime of lithium-ion battery packs in electric vehicles, especially under high charge/discharge conditions. In this regard, this study investigates a nanofluid-based cooling system for a battery module operating under 5C discharge rate. Batteries in a module are placed in a wavy cooling channel, and the proposed design is analysed for different parameters, including coolant mass flow rate (0.002 to 0.05 kg/s), nanoparticle volume fraction (0 to 0.04), battery spacing (0 to 5 mm) and channel width (4, 5 and 6 mm). For the numerical simulation, a two-dimensional …

Adaptive Active Snore Noise Control Using Microphone And Loudspeaker Arrays, Nathan Walker

All Graduate Theses and Dissertations, Fall 2023 to Present

Snoring can wreck a good night’s sleep, not just for the snorer but for their partner, and over time it can strain relationships. Common fixes like CPAP machines, nasal strips, and earplugs either have to be worn or don’t do much against the deep, low-pitched rumble that makes snoring so hard to ignore.

This research explores a different approach, a device that doesn’t need to be worn at all. It uses a small set of microphones to listen to the snoring and a set of speakers to play back carefully timed anti-snore noise, which is sound designed to cancel out …

Scalable And Interpretable Fraud Detection In Fintech: Evidence From A Hybrid Tabnet–Graph Neural Network Framework, Haseeb Ahmad, Istiaque Bhuiyan, Tanvir Bhuiyan, Ariful Hoque

Research outputs 2022 to 2026

This study proposes a fraud detection framework for FinTech that integrates tabular deep learning with relational graph reasoning. We address a key limitation of state-of-the-art tabular fraud models: their assumption that transactions are independent, despite evidence that modern fraud often arises from coordinated infrastructure reuse (e.g., shared devices, email domains, accounts, and addresses). Using the IEEE-CIS Fraud Detection dataset (≈590,540 e-commerce transactions), we develop a hybrid architecture that combines TabNet, chosen for its built-in interpretability on tabular data, with a GraphSAGE encoder trained on a leakage-free heterogeneous entity graph constructed strictly from historical training transactions. Unseen entities in validation and …

Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni

Research outputs 2022 to 2026

This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of …

Dataset For Integrity Attacks On Time Synchronized Synchrophasor Data, Taylah Griffiths, Mohiuddin Ahmed, Chadni Islam

Research outputs 2022 to 2026

Phasor measurement units, also known as synchrophasors, are a vital component within smart grids to determine the stability of the grid. These devices send synchrophasor data to phasor data concentrators that collate and analyse the data. Recently, synchrophasor communication data has become beneficial for the research community. However, datasets covering cyberattacks on synchrophasor data are not public. Having access to this data would aid in investigating mitigations against cyberattacks. This paper describes a public specialized dataset, known as ECU-PMU-FDI/TSA. The dataset contains synchrophasor communication data for cybersecurity mitigation testing. Three hours of communication data was captured, from a simulated testbed. …

Evolving Ai Integration In Complex Medical Decision-Making And Multidisciplinary Transplant Care: A Systematic Review Of Human-Ai Collaboration, Rachel L. Dzieran, Cihan H. Dagli, Robert J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: Artificial intelligence (AI) in healthcare has evolved dramatically from early expert systems, which were initially considered replacements for clinical judgment, to today's collaborative frameworks that aim to augment physician decision-making. This evolution is particularly crucial in domains such as transplant surgery, where decisions carry irreversible consequences and require the integration of complex, often ambiguous data. Drawing on peer-reviewed literature from 2019 to 2025, we conducted a systematic review that analyzed key elements distinguishing successful human-AI partnerships from those that fail. Recent Findings: The ideal balance incorporates human expertise into AI systems through weighted integration approaches, rather than …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Switching Configurations For Reconfigurable Battery Packs: A Review, Kenneth Tetteh Akiti, Quoc Viet Phung, Iftekhar Ahmad, Daryoush Habibi

Research outputs 2022 to 2026

Conventional Battery Energy Storage Systems (BESS) are designed with fixed cell topologies, where the electrical connection between cells remains unchanged throughout their life. Although Battery Management Systems (BMS) and conventional cell-balancing techniques are employed to monitor and maintain performance, they often fail to address key challenges such as uneven cell aging, capacity mismatch, and fault isolation that arise especially during the second life of a battery pack. These limitations can result in reduced efficiency, reduced reliability, and shortened battery life. As large-scale battery packs become increasingly common in Electric Vehicles (EVs), smart grids, robotics, and renewable energy systems, the limitations …

Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration, Ziqiang Liu, Fujian Tang, Yufang He, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Liquefied petroleum gas (LPG) is a highly flammable fuel widely used for cooking, heating and transportation, making real-time leak detection essential for preventing fire, explosion, and suffocation hazards. In this study, a room-temperature no-core fiber (NCF) sensor coated with CoFe_1.96La_0.04O₄/LaFeO₃ heterostructures was developed for LPG detection. The heterostructures were characterized using XRD, Raman spectroscopy, SEM, TEM, XPS, PL spectroscopy, and UV–vis spectroscopy. Experimental results showed that La incorporation and heterostructure formation refined the particles size, improved surface accessibility, and modulated the electronic structure and band gap, thereby enhancing LPG adsorption, carrier redistribution, and …

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Two-Stage Stochastic Programming For Resource Allocation In Mobile Underwater Acoustic Networks, Sadaf Vahabli, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi

Research outputs 2022 to 2026

Underwater Acoustic Networks (UANs) enable long-range communication for a range of applications. However, UANs are severely limited by scarce acoustic spectrum, which is shared with marine animals and can lead to disruptive interference, contributing to anthropogenic ocean noise. In addition, the underwater environment is highly dynamic, where: marine-animal presence is uncertain, channel conditions fluctuate, and Doppler effects degrade communication reliability. Prior UAN studies have addressed these challenges separately, despite their combined effect on resource allocation. Accordingly, this paper proposes a two-stage Scenario-based Stochastic Programming (SSP) framework with a hybrid risk approach that jointly treats these challenges within a single resource …

Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems, Mohammad Aminul Islam, Guo Shaokai, Jakaria Mahdi Imam, Mohammad Khairul Basher, Nowshad Amin, Tarek Abedin, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

The rapid development of photovoltaic (PV) systems has made them an important component of the global clean energy strategy. However, the intermittency and non-linear characteristics of photovoltaic (PV) output remain major challenges for stable renewable energy utilization. This study proposes an adaptive improved particle swarm optimization (IPSO)-based maximum power point tracking (MPPT) strategy integrated with hybrid energy storage coordination for photovoltaic systems. The IPSO introduces adaptive inertia adjustment, velocity clamping, and stagnation reinitialization, which improve the convergence robustness under dynamic irradiance and temperature conditions. The algorithm was benchmarked against Perturb & Observe (P&O), Incremental Conductance (INC), and standard PSO using …

Regularization-Based Crystallite Size Distribution Analysis Of Pt/C Catalysts From X-Ray Diffraction, Cheng-Long Ma, Wei-Yu Shi, Zhong-Jun Hou

Journal of Electrochemistry

Accurate determination of the platinum crystallite size distribution in carbon-supported platinum (Pt/C) catalysts is critical for evaluating both the initial performance and long-term durability of proton exchange membrane fuel cells (PEMFCs). Conventional characterization approaches—including transmission electron microscopy (TEM), small-angle X-ray scattering (SAXS), and the Scherrer equation—are limited by restricted statistical sampling, sensitivity to support interference, or the inability to resolve the full breadth of the size distribution. In this work, we present a regularization-based inversion framework that extracts the volume-weighted crystallite size distribution directly from X-ray diffraction (XRD) line profiles, without requiring any a priori assumption regarding the functional form …

Influence Of Particle Properties And Grain Size On Aggregation In Dry Particle-Laden Volcanic Jets, Md Miraz Hossain, Stephen A. Solovitz, Josef Dufek, Joshua S. Mendez Harper, Alexa R. Van Eaton, Mary C. Benage, Larry G. Mastin, Benjamin J. Andrews

Electrical and Computer Engineering Faculty Publications and Presentations

Explosive volcanic eruptions can inject large amounts of ash into the atmosphere. These suspended particles pose hazards to aircraft, so a better understanding of the ash residence time and transport distance is needed. Fine particles combine to form larger aggregates, altering their settling behavior. Ash aggregation is influenced by liquid bonding, electrostatic forces, and preferential concentration driven by turbulence. We examine particle aggregation through controlled, low-humidity experiments at similar particle-fluid scaling to conditions near a volcanic vent. Particle-laden jets used compressed air containing three types of particles at controlled mass loadings: hollow glass spheres (∼10 μm diameter), solid nickel spheres …

Integrated Automation Framework For Generation Retirement Studies In Transmission Planning, Mohammed Sleiman, Tianwei Xia, Zhangxin Zhou, Nathaniel Rice

Electrical and Computer Engineering Faculty Research & Creative Works

Generation retirement studies are a critical part of long-term transmission planning, as power systems transition toward higher penetration of renewable energy and the retirement of conventional generation. However, existing study workflows are often fragmented across multiple tools and platforms such as PSS/E, TARA, Python, and Excel resulting in time-intensive processes, limited scalability, and reduced reproducibility. This paper showcases an integrated automation tool developed for generation retirement studies that is designed to streamline and unify the end-to-end analytical workflow.

The proposed framework consolidates key study components, including generator retirement modeling, power flow redispatch, contingency analysis (N-1 and N-1-1), and mitigation cost …

Comprehensive Variable-Temperature Raman And Spectroscopic Ellipsometry Investigation Of Bulk Undoped, Fe-Doped, And Ge-Doped Gan: Correlated Phonon, Carrier, Optical, And Disorder Dynamics, Manika Tun Nafisa, Sm Atiqur Rahman, Zhe Chuan Feng, Sandip Das, James N. Hilfiker, Nina Jong, Ian T. Ferguson, Benjamin Klein

Faculty Articles

Bulk gallium nitride (GaN) substrates with controlled electrical compensation and doping are foundational materials for high-power electronics, optoelectronics, and emerging spintronic devices. Despite extensive studies on epitaxial GaN thin films, a complete and correlated understanding of crystal, phonon, free-carrier, birefringence, optical, and disorder-driven processes in high-quality bulk GaN crystals remains limited. In this work, a comprehensive temperature-dependent (25–300 °C) investigation of free-standing bulk undoped, Fe-doped, and Ge-doped GaN substrates using Raman spectroscopy, spectroscopic ellipsometry (SE), and atomic force microscopy (AFM) has been presented. A detailed analysis of phonon evolution, apparent Raman-shift-derived biaxial stress and in-plane strain, longitudinal optical phonon–plasmon coupling …

China’S Semiconductor Supply Chain Landscape And Strategies For Enhancing Global Competitiveness, Su Zhang, Ziyan Yang, Yifan Sun, Yan Xia, Huijuan Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Against the backdrop of accelerating global digital transformation, intelligent upgrades, and intensifying geopolitical competition, the semiconductor supply chain has become the focal point of global technological, economic, and security dynamics. This study systematically examines the evolution of the global semiconductor supply chain, assesses security risks in China’s semiconductor industry, and analyzes the impact of China-US semiconductor decoupling using a hypothesis extraction approach. Based on these findings, it proposes strategic pathways to enhance China’s semiconductor competitiveness. Key findings include the following: (1) The global semiconductor supply chain exhibits both “regional concentration” and “industry fragmentation”. The US and Europe dominate upstream segments, …

Estimation Of Unmeasurable External Disturbances Of A Dynamic Object Based On A Robust Adaptive Kalman Filter, Bunyod Mamurjon Ugli Buronov

Technical science and innovation

This article considers the problem of directly estimating unmeasurable external disturbances acting on a dynamic object under the condition that the state vector of the object is available for measurement. In the considered case, the problem is reduced to the estimation of an unknown input of a dynamic system. It is shown that when the system state is measurable, both a direct inversion scheme based on the object’s dynamic equation and filtering methods that eliminate the need for coarse numerical differentiation can be applied. For slowly varying disturbances, a random walk model with a small process noise covariance is proposed, …

Technical, Environmental And Institutional Readiness For Nuclear Power Deployment In Seismically Active Power Systems, King Harold A. Recto, Izech Brian O. Edwin

Electronics, Computer, and Communications Engineering Faculty Publications

The deployment of nuclear power in seismically active power systems presents significant engineering, environmental, and institutional challenges. Although nuclear energy offers a low-carbon option capable of supporting long-term energy transition goals, its adoption requires careful evaluation of readiness factors beyond reactor technology alone. This study investigates the technical, environmental, and institutional determinants influencing nuclear power deployment in seismically active regions. A systematic review of engineering, environmental, and policy literature was conducted to identify key factors affecting nuclear energy integration, including grid capacity requirements, seismic safety considerations, hydrological conditions for reactor cooling, and long-term radioactive waste management strategies. These factors are …

Integrated Evaluation Of Rooftop Solar Power Generation System Performance In Tropical Climate Using Geometric, Electrical, And Environmental Parameters, Ayu N. Sari, Ilham R. Fadhlurrahman, Surya Pinanggi, Ermanu A. Hakim, Haneef Nouval Alannibras Humaidi

Journal of Mechanical Engineering Science and Technology (JMEST)

The increasing demand for electrical energy in the commercial sector has encouraged the utilization of rooftop Photovoltaic (PV) systems as a sustainable energy solution in tropical climate regions. However, rooftop PV performance is influenced by the interaction of geometric, electrical, and environmental parameters, which may affect system efficiency. This study analyzes the performance of a rooftop PV system under tropical climate conditions using PVsyst simulation and actual monitoring data collected over 30 days. The research was conducted on an on-grid rooftop PV system with a capacity of approximately 135 kWp, consisting of 217 photovoltaic modules and three inverters with a …

Analysis And Study Of The Content Of Chloride Salts In Oil, Natalia Evgenievna Sheina, Muborak Akramovna Mirshomilova

Technical science and innovation

The article addresses the critical issue of crude oil quality control, specifically focusing on the determination of chloride salts (sodium, calcium, and magnesium), which exert a destructive impact on processing equipment. The paper provides a detailed analysis of the adverse effects of salts, which lead to severe equipment corrosion, scaling, and a reduced yield of valuable oil fractions. The chemical principles and specific applications of two standardized methods for analyzing aqueous extracts according to GOST 21534-2021 and ASTM D3230 are described: indicator (argentometric and mercurimetric) and potentiometric titration. The experimental section presents the results of a comparative analysis of crude …

Automatic +1 Diffraction Order Detection In Off-Axis Digital Holographic Interferometry Using An Energy-Based Spectral Model, Nigora Alimdjanovna Akbarova, Dilnoza Ibrokhim Kizi Abdulkhayeva

Technical science and innovation

This paper presents an automatic +1 diffraction order detection algorithm for off-axis digital holographic interferometry (DHI Manual spectral filtering is widely used to find out the desired order of diffraction in the Fourier domain in conventional digital holographic reconstruction. Nevertheless, this approach is very subjective and must be subject to expert guidance, thus, the reconstruction reproducibility and stability can often deteriorate. To address these limitations, this designed scheme constructs a spectral model utilizing energy-maximization as well as adaptive DC suppression and dynamic filter radius estimates. The algorithm itself can automatically observe the distribution of energy in the hologram spectrum and …

Analysis And Optimization Of Intelligent Control Of The Drying Process Under Uncertainty, Azizbek Nodirbekovich Yusupbekov, Marufjon Kobuljonovich Shodiev, Khusniddin Mamarasul Ugli Esonov

Technical science and innovation

This section proposes a multi-criteria Pareto-optimization algorithm, integrated with Herbert Simon's four-stage decision-making scheme (Intelligence–Design–Choice–Implementation) and an ANFIS-based adaptive controller, for simultaneously optimizing the mutually conflicting quality, energy, and time criteria of the wheat-drying process. The algorithm for constructing the set of Pareto-optimal solutions and selecting the compromise solution closest to the ideal point is presented step by step. The implementation of the ANFIS controller in the MATLAB/Simulink environment is comprehensively verified through a simulation block diagram, the Rule Viewer, the Surface Viewer, the training error-function graph, the RMSE convergence graph, and a learning-curve analysis. Training was carried out on …

Evaluation Of The Metrological Characteristics Of An Ultrasonic Flowmeter For Water Resources, Makhsud Idrisovich Makhmudov, Uktam Farkhodovich Mamirov, Siroj Sobirovich Nurov

Technical science and innovation

This paper presents the results of evaluating the metrological characteristics of a developed ultrasonic flowmeter intended for measuring water flow in open channels. The study analyzes the main sources of measurement errors and classifies them into methodological, instrumental, additional, systematic, and random components. Experimental investigations were carried out to estimate the random and systematic errors under steady-state flow conditions. Using the least-squares method, the systematic error was separated into additive and multiplicative components, providing a basis for calibration and correction of the measurement results. The reliability of the developed measuring instrument was evaluated using the failure rate method based on …

Development Of An Experimental Stand For The Study Of The Directions Of Movement And Velocity Of Air Flows In The Pneumatic Channel Of The Final Aspiration Of The Muz-16 Air Sieve Separator, Hanna Borisovna Torgan, Zulfiya Kakhramonovna Ergasheva

Technical science and innovation

The article presents the results of experimental studies on the rheological properties of pasta dough obtained from various types of wheat flour (bakery highest grade, as well as durum varieties of Belarusian selection). The regularities of changes in the yield shear stress, plastic viscosity, and shear rate of the semi-finished product were studied depending on the key technological factors of extrusion: moisture content (0.28–0.335 kg/kg), temperature (25–55 °C), and discharge pressure (up to 88 · 10^-5 Pa). The operating principle and design features of the modernized pressing unit and die using special converging-diverging (confuser-diffuser) inserts (according to the patents …

Research On The Effectiveness Of Various Methods For Primary Processing Of Silkworm Cocoons, Doston Ishmukhammat Ugli Samandarov

Technical science and innovation

This article presents the results of experimental studies of the primary processing (killing) of silkworm pupae using existing technological methods, as well as three different combinations of infrared (IR) and ultrasound (US). A series of pilot studies was conducted in the laboratory of the Department of Service Technology at Tashkent State Technical University on nine cocoon samples using existing technological equipment and an experimental setup developed under project AL-8724053050 and based on the combined effects of infrared radiation and ultrasound. A comparative evaluation of the studied processing methods was conducted based on the degree of pupal killing, moth hatching, process …

Mathematical Modelling Of Nitrification And Denitrification Processes Based On Neuro-Fuzzy Bioreactor Models, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon Ugli Mannobjonov

Technical science and innovation

This paper presents the development and investigation of hybrid neural network and fuzzy models for the mathematical modelling of nitrification and denitrification processes in a biological wastewater treatment bioreactor. A comprehensive approach is proposed, integrating a mechanistic model of the ASM1/ASM2d type with neural networks (LSTM and Gaussian Process Regression), as well as a fuzzy control system based on an extended set of expert rules. A digital twin of the bioreactor was developed to allow for the prediction of the dynamic behavior of key parameters such as NH₄⁺, NO₃⁻, dissolved oxygen, etc. within a prediction range of 1 to 12 …

Investigation Of The Production Technology Of Environmentally Safe Urethane Oligomers Based On Local Raw Materials, Bakhtiyor Kudratovich Shaykulov, Dilafruza Ruziboevna Akbarova Gulboeva, Fayzulla Nurmuminovich Nurqulov

Technical science and innovation

This paper investigates the step-by-step poly condensation pathway for synthesizing environmentally friendly, non-isocyanate urethane oligomers derived from local and safe raw materials: urea and ethylene glycol. The influence of thermodynamic parameters on the target product yield was systematically evaluated to determine the optimum technological matrix. Specifically, a 1:2 reactant mass ratio, a stable stationary temperature of 150-155 °C, and a reaction duration of 2 hours under an inert nitrogen atmosphere resulted in a sustainable and reproducible yield of 72%. Thermal degradation and competitive side-product condensations were activated above 160 °C, leading to a sharp drop in overall chemical efficiency. The …

Evaluation Of Level Measurement Uncertainty For Three Types Of Laser Level Meters Using The Gum Methodology: Calculated Uncertainty Budgets, Uncertainty Profile, And Hardware Component Requirements, Lazizbek Furkatjanovich Saidoripov, Barat Makhmudovich Akhmedov

Technical science and innovation

A methodology is presented for evaluating the uncertainty of liquid petroleum product level measurements using laser level meters based on different measurands’ informative parameters: propagation time, phase difference, and image coordinates. Based on analytical expressions for error components and a traceability chain to the national length standard, calculated uncertainty budgets are developed in accordance with JCGM 100 for time-of-flight, phase-based, and laser–television level meters. Under the assumed input conditions, the expanded uncertainties (k = 2) are 1.66, 0.73, and 1.02 mm, respectively. For the laser–television level meter budget, the Gaussian approximation is verified using the Monte Carlo method (JCGM 101): …