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Logic gates can be written in terms of complex differential operators, where the inputs and outputs are holomorphic functions with several variables. Using the polar representation of complex numbers, we arrive at an immediate connection between the oscillatory behavior of the system and logic gates. We discuss the universality of this formalism in a variety of computing systems. [ABSTRACT FROM AUTHOR]

In this work, we present a comprehensive study of the commutativity of fractional-order linear time-varying systems (LTVSs). Commutativity is a fundamental property in the analysis and control of dynamic systems and is often used to simplify the design of controllers. Fractional-order systems, which are characterized by a noninteger-order derivative, have been widely studied in recent years due to their ability to model a wide range of phenomena. However, the commutativity of fractional-order LTVSs has not been widely explored. In this work, we present a comprehensive study of the commutativity of fractional-order LTVSs. We first provide a mathematical definition of commutativity for these systems and demonstrate that it is equivalent to the commutativity of their transfer functions. We then propose a method for verifying the general condition for commutativity of fractional-order LTVSs under zero initial conditions (ICs) and prove it mathematically. Based on our findings, we realized that the commutative requirements, properties, theories, and conditions are general for fractional-order LTVSs, please observed that some fractional-order LTVSs are commutative, some are not commutative, while some are commutative under certain conditions. Based on this fact, we can say that not all fractional-order LTVSs are commutative.We apply explicit commutative results to several examples of fractional-order LTVSs. Our theoretical and simulation results show a good agreement and prove that our fractional-order LTVSs are commutative under certain conditions, moreover, the commutativity property holds for certain conditions and classes of fractional-order LTVSs, but not for others. Because of the application of fraction commutativity in various fields of science and engineering, we find it necessary to come up with explicit results for the first time. [ABSTRACT FROM AUTHOR]

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Quantum computing, as a forefront field in quantum technology, has made significant progress in simulating physical systems, yet it still faces technical challenges such as hardware noise and quantum errors. This review discusses the latest advancements in quantum computing for simulating physical systems, with a focus on the application of quantum-classical hybrid algorithms and error mitigation techniques, exploring their strengths and limitations across various physical systems. The review covers the simulation of molecular systems using superconducting quantum computers, many-body problems in condensed matter systems, solving equations in complex fluid dynamics, and applications in astrophysics and high-energy physics. For molecular systems, variational quantum algorithms (VQE) are widely used to solve the ground state energy of multi-electron systems, with error mitigation methods improving simulation accuracy. In condensed matter systems, quantum computing has shown high precision and efficiency in simulating strongly correlated spin models, such as the Heisenberg and Ising models, achieving unprecedented accuracy in larger spin chain simulations. In the field of fluid dynamics, research indicates that quantum-classical hybrid algorithms can accelerate the solution of the Navier-Stokes equations to some extent, providing new tools for future fluid dynamics studies. In astrophysical simulations, quantum computing has been used to study the properties of black holes and dark matter, demonstrating potential exponential acceleration, which offers new possibilities for understanding physical phenomena under extreme conditions in the universe. In high-energy physics, quantum computing shows promising applications in solving problems like the Schwinger model and has begun exploring the potential of quantum machine learning in analyzing high-energy experimental data. This review provides a comprehensive perspective on the applications of quantum computing in simulating various physical systems, and outlines future directions and technical challenges.

This paper aims to introduce a new fractional extension of the interval Hermite–Hadamard ( H H ), H H –Fejér, and Pachpatte-type inequalities for left- and right-interval-valued harmonically convex mappings ( L R I V H convex mappings) with an exponential function in the kernel. We use fractional operators to develop several generalizations, capturing unique outcomes that are currently under investigation, while also introducing a new operator. Generally, we propose two methods that, in conjunction with more generalized fractional integral operators with an exponential function in the kernel, can address certain novel generalizations of increasing mappings under the assumption of L R I V convexity, yielding some noteworthy results. The results produced by applying the suggested scheme show that the computational effects are extremely accurate, flexible, efficient, and simple to implement in order to explore the path of upcoming intricate waveform and circuit theory research. [ABSTRACT FROM AUTHOR]

Different chemical, physical, and physico-chemical methods with addition of optical methods have been used for decades for the development of latent fingerprints (LFPs), even though the choice of a method depends on various factors (type and structure of the surface, external conditions, donor etc.). However, a universal system has not yet been fabricated, while many of those already used are toxic to the humans and the environment. Recently, researchers designed formulations based on (bio)polymeric materials and their specific properties, suitable for targeted interaction with fingerprint (FP) sweat and lipid residues. Some research groups produced fluorescent properties of particular polymeric materials to map sweat pores, while others encapsulated/incorporated dyes, pigments, etc. into polymeric matrix to obtain formulations of desired color and properties. Additionally, polymer micelles have become interesting due to their amphiphilic properties and the ability to incorporate compounds which could enable multi-colored emission brightness. Nevertheless, (polymeric) nanomaterials are currently of a great importance in material science world, due to specific optical and electronic properties convenient for interaction with FP residues found on different (multi-colored, electroconductive, etc.) substrates. This paper focuses on (bio)polymer-based systems used to develop LFPs, different approaches of research groups and future possibilities to create the optimal system for specified purpose.

This paper aims to introduce a new fractional extension of the interval Hermite–Hadamard (HH), HH–Fejér, and Pachpatte-type inequalities for left- and right-interval-valued harmonically convex mappings (LRIVH convex mappings) with an exponential function in the kernel. We use fractional operators to develop several generalizations, capturing unique outcomes that are currently under investigation, while also introducing a new operator. Generally, we propose two methods that, in conjunction with more generalized fractional integral operators with an exponential function in the kernel, can address certain novel generalizations of increasing mappings under the assumption of LRIV convexity, yielding some noteworthy results. The results produced by applying the suggested scheme show that the computational effects are extremely accurate, flexible, efficient, and simple to implement in order to explore the path of upcoming intricate waveform and circuit theory research.

The necessary and sufficient conditions for decomposing a fourth-order (FO) linear time-variant system (LTVS) in the form of cascade connection of a first-order system and a third-order system that are commutative are expressed explicitly in this paper. Some additional conditions are also derived for a valid decomposition when the initial conditions are different from zero. Further, explicit formulas are derived for the determination of the decomposed subsystems. The paper also investigated the effects of changing the connection order on the sensitivity and disturbance properties. Theoretical results about the decomposition are supported and illustrated by considering various examples. [ABSTRACT FROM AUTHOR]

Second-order oscillatory problems have been found to be applicable in studying various phenomena in science and engineering; this is because these problems have the capabilities of replicating different aspects of the real world. In this research, a new hybrid method shall be formulated for the simulations of second-order oscillatory problems with applications to physical systems. The proposed method shall be formulated using the procedure of interpolation and collocation by adopting power series as basis function. In formulating the method, off-step points were introduced within the interval of integration in order to bypass the Dahlquist barrier, improve the accuracy of the method and also upgrade the order of consistence of the method. The paper further validated the some properties of the hybrid method derived and from the results obtained; the new method was found to be consistent, convergent and stable. The simulation results generated as a result of the application of the new method on some second-order oscillatory differential equations also showed that the new hybrid method is computationally reliable. [ABSTRACT FROM AUTHOR]

It is a known fact that in most cases, to integrate an oscillatory problem, higher order A-stable methods are often needed. This is because such problems are characterized by stiffness, chaos and damping, thus making them tedious to solve. However, in this research, an accuracy-preserving relatively lower order Block Hybrid Algorithm (BHA) is proposed for solution of second-order physical systems with oscillatory solutions. The sixth order algorithm was derived using interpolation and collocation of power series within a single step interval [tn; tn+1]. In order to circumvent the Dahlquist-barrier and also obtain an accuracy-preserving algorithm, four off-step points were incorporated within the single step interval. A number of special cases of oscillatory problems were solved using the proposed method and the results obtained clearly showed that it outperformed other existing methods we compared our results with even though the BHA is of lower order relative to such methods. Some of the second-order physical systems considered were the Kepler, Bessel and damped problems. Some important properties of the BHA were also analyzed and the results of the analysis showed that it is consistent, zero-stable and convergent. [ABSTRACT FROM AUTHOR]

Several mathematical models have been developed for applications in the hydraulics of irrigation systems and several performance indicators of these models are used and suggested by the literature. Thus, the objective of this work was to investigate the performance of statistical indicators for the evaluation of models in irrigation hydraulics. For this, three case studies which represent typical irrigation hydraulics modeling were used to assess the indicators. A set of indicators were analyzed: a) difference-based: mean absolute error, mean square error, root mean square error, scaled root mean square error, and percent mean absolute error; b) efficiency-based: Nash-Sutcliffe and Legates-McCabe; c) correlation coefficient (r); d) coefficient of determination (R2); e) index of agreement index (d); f) Camargo and Sentelhas index (c); and g) graphical methods: regression error characteristic curve based on relative absolute error and 1:1 scatter plot. For the evaluated cases, which are physical phenomena, differentiable indicators are similar measures and it is appropriate to report either or both indices. The assessment of models must also be supported by graphical analysis, which shows the real scenario of errors in the model evaluation processes. Efficiency-based indicators, r, R2, c, and d are not recommended and should be avoided in modeling of irrigation hydraulics. [ABSTRACT FROM AUTHOR]

• A graph transformer-based surrogate model is proposed to predict the long-term evolution process of physics systems. • The graph transformer with attention mechanism is proposed to aggregate information from neighboring nodes. • A multi-step prediction strategy is employed in the loss function to ensure robust long-term prediction capability. • Innovative symlog and symexp functions are proposed to predict stress in solid mechanics. • The proposed model can achieve high-accuracy and efficient long-term evolution prediction of physical systems. Predicting physical systems over long-term horizons has a significant challenge. Although prevalent machine learning techniques, such as Physics-Informed Neural Networks (PINNs), can achieve high accuracy, they primarily focus on single-step solutions and entail high computational costs. To address this gap, we propose a novel surrogate model leveraging graph representation for mesh-based physical systems. The proposed model incorporates Graph Transformer with attention mechanisms to aggregate information from neighboring nodes efficiently. Furthermore, we employ a multi-step prediction strategy in the loss function formulation to ensure robust long-term prediction capabilities. Additionally, in order to predict stress in solid mechanics, innovative symlog and symexp functions are proposed to enhance the robustness and reliability of the proposed model. Numerical results indicate that the proposed model can achieve high-accuracy and efficient long-term evolution prediction of physical systems. [ABSTRACT FROM AUTHOR]

Wireless communication technologies, smart sensors, enormously enhanced computational capabilities, intelligent controls merge to form Cyber-Physical Systems (CPSs). The synergy achieved due to this integration will considerably transform how humans’ interaction with engineered systems in future smart cities. Such cities will leverage technologies to design, develop, and implement intelligent solutions to provide inclusive development, efficient community infrastructure, and a clean and sustainable environment. One of the domains likely to witness paradigm- shift in future smart cities is transport. The development of urban structures, functionality, and prosperity are intricately connected to how the city designs its mobility infrastructure. Shortly, all vehicles and roadside infrastructures in a city-wide ITS will be enabled with integrated smart sensors, edge computing devices and communication units to provide diversified and inclusive services to its residents. Nonetheless, due to the high heterogeneity and complexity of cross-cutting aspects of CPS, the transportation domain is susceptible to cyber vulnerabilities, threats, illegal access, cyber-attacks, unauthorized information sharing, and so on. This paper attempts to understand smart CPS-enabled transportation systems, it’s conceptual framework, the connected and automated vehicles and other associated technologies and communication networks. Finally, we present the expected demands of the transportation domain in a future smart city and the capabilities of CPS in a demand-supply framework. However, the major intellectual challenge lies in effectively designing-developing-deploying models and algorithms to harness the powers of the integrated TCPS system implemented in the intended environment.

It is a known fact that in most cases, to integrate an oscillatory problem, higher order A-stable methods are often needed. This is because such problems are characterized by stiffness, chaos and damping, thus making them tedious to solve. However, in this research, an accuracy-preserving relatively lower order Block Hybrid Algorithm (BHA) is proposed for solution of second-order physical systems with oscillatory solutions. The sixth order algorithm was derived using interpolation and collocation of power series within a single step interval [tn; tn+1]. In order to circumvent the Dahlquist-barrier and also obtain an accuracy-preserving algorithm, four o-step points were incorporated within the single step interval. A number of special cases of oscillatory problems were solved using the proposed method and the results obtained clearly showed that it outperformed other existing methods we compared our results with even though the BHA is of lower order relative to such methods. Some of the second-order physical systems considered were the Kepler, Bessel and damped problems. Some important properties of the BHA were also analyzed and the results of the analysis showed that it is consistent, zero-stable and convergent

Generating pressure transient response for an interpretation model to describe essential features of a reservoir system accurately is often difficult. It is generally due to the inaccessibility of standard pressure transient analysis tools due to the cost, and even when accessible, they are constrained to its workflow and limitations. This study presents an alternative to standard industry tools to determine transient pressure response for a given rate history. A reservoir model for a single well with constant skin and wellbore storage producing a varying step rate in a semi-infinite acting reservoir with a sealing fault was used as a case study. The well is also assumed to be producing above saturation pressure from a reservoir saturated with slightly compressible fluid hence having constant fluid properties. The method discussed in this study can be applied to well-test interpretation models with an analytical constant terminal rate solution producing at variable step rates from a reservoir having constant rock and fluid properties. The results show conformance with that of standard industry software, and diagnostic plots of the simulated data set can help engineers plan well-test jobs and study the behavior of different reservoir models. Moreover, the program can be modified and used to regress observed pressure response with a selected model. The approach suggested by this study is a perfect alternative where time and cost are constraints.

Several mathematical models have been developed for applications in the hydraulics of irrigation systems and several performance indicators of these models are used and suggested by the literature. Thus, the objective of this work was to investigate the performance of statistical indicators for the evaluation of models in irrigation hydraulics. For this, three case studies which represent typical irrigation hydraulics modeling were used to assess the indicators. A set of indicators were analyzed: a) difference-based: mean absolute error, mean square error, root mean square error, scaled root mean square error, and percent mean absolute error; b) efficiency-based: Nash-Sutcliffe and Legates-McCabe; c) correlation coefficient ( ); d) coefficient of determination ( ); e) index of agreement index ( ); f) Camargo and Sentelhas index ( ); and g) graphical methods: regression error characteristic curve based on relative absolute error and 1:1 scatter plot. For the evaluated cases, which are physical phenomena, differentiable indicators are similar measures and it is appropriate to report either or both indices. The assessment of models must also be supported by graphical analysis, which shows the real scenario of errors in the model evaluation processes. Efficiency-based indicators, , , , and are not recommended and should be avoided in modeling of irrigation hydraulics.

Second-order oscillatory problems have been found to be applicable in studying various phenomena in science and engineering; this is because these problems have the capabilities of replicating different aspects of the real world. In this research, a new hybrid method shall be formulated for the simulations of second-order oscillatory problems with applications to physical systems. The proposed method shall be formulated using the procedure of interpolation and collocation by adopting power series as basis function. In formulating the method, off-step points were introduced within the interval of integration in order to bypass the Dahlquist barrier, improve the accuracy of the method and also upgrade the order of consistence of the method. The paper further validated the some properties of the hybrid method derived and from the results obtained; the new method was found to be consistent, convergent and stable. The simulation results generated as a result of the application of the new method on some second-order oscillatory differential equations also showed that the new hybrid method is computationally reliable.

Physical systems and signals are characterized by complex functions of the frequency in the harmonic domain. The extension of such functions to the complex frequency plane, and in particular expansions and factorized forms of the harmonic-domain functions in terms of their poles and zeros, is of high interest to describe the physical properties of a system, and study its response dynamics in the temporal and harmonic domains. In this work, we start from a general property of continuity and differentiability of the complex functions to derive the multiple-order singularity expansion method. We rigorously derive the common singularity and zero expansion and factorization expressions, and generalize them to the case of singularities of arbitrary order, while deducing the behavior of these complex frequencies from the simple hypothesis that we are dealing with physically realistic signals.

Decomposition is an important tool that is used in many differential systems for solving real engineering problems and improving the stability of a system. It involves breaking down of high-order linear systems into lower-order commutative pairs. Commutativity plays an essential role in mathematics, and its applications are extended in physical science and engineering. This paper explicitly expresses all form of necessary and sufficient conditions for decomposition of any kind of fourth-order linear time-varying system as commutative pairs of two second-order systems. Regarding the nonzero initial conditions, additional requirements are derived in order to satisfy the decomposition process. In this paper, explicit method for reducing fourth-order linear time-varying systems (LTVS) into two second-order commutative pairs is derived and solved. The method points out the effect of disturbance and sensitivity on the systems and also highlights the necessary and sufficient conditions for commutativity of the decomposed systems. The results are illustrated by solving some examples. [ABSTRACT FROM AUTHOR]

Cyber‐physical systems (CPS) refer to the incorporation of computing systems in physical world procedures. In the present systems, researchers are facing some difficulties, such as their use in school and colleges, which need to be resolved in CPS. In this paper, we offer a model for the inclusion of physical settings with an artificial intelligent adjustment system to bridge the gap between teaching and intelligent educational cyber systems. Furthermore, this paper provides a definition and description of Adaptive English Cyber personalized systematic Algorithm with nano‐class. Finally, we develop a prototype of advanced educational cyber‐physical system using Intelligent Classification Algorithm for the English course in the college for effective teaching. [ABSTRACT FROM AUTHOR]

The smart grid is an upgraded concept of electricity network with tight coupling among information, control, and bi-directional communication technologies. Along with the silent features of the on-going smart grid, cyber–physical security appears to be a deep concern due to its significant dependence on sensing technologies, complex networks of computers, intelligence, and wide-area communication infrastructures. Moreover, the smart grid is an extensive critical infrastructure and vulnerable to coordinated cyber–physical attacks. As a result, cyber–physical attacks cause significant threats to the confidentiality and integrity of the power data, including power outages, cascading failures, and unnecessary expenditure. In this study, security issues of smart grid, including cyber–physical interdependency, attack varieties, detection methods, requirements, standards, challenges, and future prospects, are taken into consideration for both cyber and physical systems, aiming to provide an extensive understanding of vulnerabilities and solutions for the smart power grid. By revealing the inherent features of cyber–physical security in the smart grid, this survey study is addressed to facilitate future research in these two areas.

The authors tackle time synchronisation of two (possibly non‐identical) second‐order dynamical systems whose state space possess the structure of a Lie group. Synchronisation is treated as a non‐linear control problem on Lie groups. They present a control theory inspired by the proportional–integral–derivative (PID) regulation principle. The resulting L‐PID control scheme is applied to sync the rotational component of motions in physical systems. A model‐dependent version of the L‐PID, equipped with a dynamics‐cancelling component, is theoretically proven to converge to zero control error by a Lyapunov stability analysis. Furthermore, they present Lie‐group‐tailored numerical techniques to implement the devised PID regulation theory and test such numerical schemes on two dynamical systems, namely, a gyrostat satellite and a quadrotor drone. As a further extension, they present an empirical translational synchronisation algorithm for two drones based on a pair of concurring L‐PID and projected‐PID controllers. [ABSTRACT FROM AUTHOR]

Our aim in this paper is to replace the old concept of truth in mathematics, based on the Set Structure provided with idea of true and false characterized by the presence of a characteric function Ω = { 0 , 1 } , by a mathematical structures founded on the idea of Topos, the triple structure { X : (Y , T , d n) } and the notion of Gradual Truth or Steps from the truth. Our motivations is to understand the mathematical structures underlying the emergence's mechanism and phenomena. We think that this approach could be useful to better appreciate the subtleties of the notion of truth and gives us a better understanding of the complex and changing phenomena. [ABSTRACT FROM AUTHOR]

Modern modeling languages for general physical systems, such as Modelica, Amesim, or Simscape, rely on Differential Algebraic Equations (DAEs), i.e., constraints of the form f (x ′ , x , u) = 0. This drastically facilitates modeling from first principles of the physics, as well as the reuse of models. In this paper, we develop the mathematical theory needed to establish the development of compilers and tools for DAE-based physical modeling languages on solid mathematical bases. Unlike Ordinary Differential Equations (ODEs, of the form x ′ = g (x , u)), DAEs exhibit subtle issues because of the notion of differentiation index and related latent equations —ODEs are DAEs of index zero, for which no latent equation needs to be considered. Prior to generating execution code and calling solvers, the compilation of such languages requires a nontrivial structural analysis step that reduces the differentiation index to a level acceptable by DAE solvers. The models supported by tools of the Modelica class involve multiple modes, with mode-dependent DAE-based dynamics and state-dependent mode switching. However, multimode DAEs are much more difficult to handle than DAEs, especially because of the events of mode change. Unfortunately, the large literature devoted to the mathematical analysis of DAEs does not cover the multimode case, typically saying nothing about mode changes. This lack of foundations causes numerous difficulties to the existing modeling tools. Some models are well handled, others are not, with no clear boundary between the two classes. In this paper, we develop a comprehensive mathematical approach supporting compilation and code generation for this class of languages. Its core is the structural analysis of multimode DAE systems. As a byproduct of this structural analysis, we propose sound criteria for accepting or rejecting multimode models. Our mathematical development relies on nonstandard analysis , which allows us to cast hybrid system dynamics to discrete-time dynamics with infinitesimal step size, thus providing a uniform framework for handling both continuous dynamics and mode change events. [ABSTRACT FROM AUTHOR]

This study presents a tool to study the cyber-physical resiliency (CyPhyR) of critical energy infrastructure system, in particular the effect of cyber attacks on the microgrid's resiliency. The developed tool enables measuring resiliency using data from cyber and physical systems and suggests control decisions for resilient planning and operation of the microgrid. The microgrid resiliency is formulated based on graph theory based indices and cyber-power system characteristics. A Common Vulnerability Scoring System based metric called the Cyber Asset Impact Potential is developed and used in the planning phase, and another metric, Cyber Impact Severity is introduced to study the system performance in the operational phase. The information from these two phases is provided to the operator to make informed and proactive decisions to ensure the resilient operation of the microgrid. The performance of the developed tool has been tested using comprehensive real-time cyber-power testbed for a Consortium for Electric Reliability Technology Solutions microgrid test system.

Decomposition is a common tool for the synthesis of many physical systems. It is also used for analyzing large-scale systems which are then known as tearing and reconstruction. On the other hand, commutativity of cascade-connected systems has gained a great deal of interest, and its possible benefits have been pointed out on the literature. In this paper, the necessary and sufficient conditions for decomposition of any third-order linear time-varying system as a commutative pair of first- and second-order systems of which parameters are also explicitly expressed, are investigated. Further, additional requirements in case of nonzero initial conditions are derived. This paper highlights the direct formulas for realization of any third-order linear time-varying systems as a series (cascade) connection of first- and second-order subsystems. This series connection is commutative so that it is independent from the sequence of subsystems in the connection. Hence, the convenient sequence can be decided by considering the overall performance of the system when the sensitivity, disturbance, and robustness effects are considered. Realization covers transient responses as well as steady-state responses. [ABSTRACT FROM AUTHOR]

Due to certain progress made in Artificial Intelligence (AI) and related fields, there is a common agreement that we are facing a blurring of the human and the artificial. This presentation will argue that this agreement is rather one that pertains to anthropomorphic notations when dealing with computers and computer-based devices, as opposed to one that is justified by engineering results. In fact, the language used to describe mechanic functions hides what ontologically occurs, and how the autonomy of humans can be endangered. The clarification intended here uses the philosophical distinction between agents and patients and translates it into the systems theoretical distinction between self-organising systems and non-self-organising entities.

In this study, a class of models governed by a second‐order (in time) evolution differential equation with damping and positive definite, self‐adjoint system operator is studied. Damping term has a special, but practically important, form of a finite sum of fractional powers of the system operator. This type of damping operator can be used to model a variety of physical phenomena related to dissipation of energy empirically observed in physical systems. It may be used to model dissipation mechanisms resulting from air damping, internal structural damping, internal viscous damping, etc. Using spectral theory of linear unbounded operators and semi‐group theory necessary and sufficient conditions of approximate controllability for second order infinite dimensional system with damping are formulated and proved. Some important, from the practical point of view, remarks and comments are also provided. In particular, necessary condition for approximate controllability is formulated and discussed. Finally, an illustrative example related to approximate controllability of distributed parameter system described by the partial differential equation with higher order spatial differential operators is presented. The example refers to a system describing dynamical behaviour of damped Kirchhoff–Love plate. The study extends earlier results on approximate controllability of damped second‐order abstract evolution dynamical systems. [ABSTRACT FROM AUTHOR]

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results. [ABSTRACT FROM AUTHOR]