Advanced Modeling Methods Research Articles

Sound propagation methods for road traffic noise auralization

When changes to an area involving an upgrade to a road network (new or existing) are planned, an assessment of the potential for change in the sound environment is carried out. However this assessment usually only considers local residents’ daily noise exposure and it can be difficult to understand what an increase of 2 dB, for example, actually means in terms of what you hear. Further to this, perceived changes in sound character in relation to road traffic and associated noise mitigation measures are not assessed by current methodologies. There has been increased interest recently in auralization as a potential environmental sound design tool. Without the existence of standardized guidance on the application of existing sound propagation models for auralization there is a potential to obtain a wide range of perceptually different results, depending on the adopted methodology. This work discusses important considerations for the auralization of road traffic noise. Accurately creating these experiences requires bringing together existing sound recordings with the latest and most advanced methods for traffic and environmental noise modeling. Here we discuss some proposed algorithms and methods for achieving this and potential improvements to the nascent methodology for the future.

AgBM-DTALite: An integrated modelling system of agent-based travel behaviour and transportation network dynamics

Advanced modelling methods and products, such as an integrated advanced travel demand model and a fine-grained time-sensitive network that can operate at statewide, metropolitan and subarea/corridor levels, are required by a number of transportation planning agencies to meet their objectives and address various key challenges. This research develops an application-ready integrated transportation model that can predict, in a future-year scenario or in a hypothetical scenario, both the changes in travel behavioural adjustments and the dynamics in traffic conditions. The integrated framework embeds theoretically sound behavioural foundation by incorporating agent-based searching, information acquisition, learning, knowledge updating and decision-making. Multidimensional travel behaviour, including mode choice, route choice, departure time choice and en-route diversion, is considered. Behavioural user equilibrium is defined without assuming perfect rationality. A dynamic traffic simulation engine is employed to model and simulate real-time traffic conditions. Data exchanges between the travel demand model and the traffic simulation are explained in detail. The integration is demonstrated using a real-world case study. Future applications should cover a wide spectrum of scenarios in transportation planning/policy and traffic operations/control analyses.

Optimization in liner shipping

Seaborne trade is the lynchpin in almost every international supply chain, and about 90% of non-bulk cargo worldwide is transported by container. In this survey we give an overview of data-driven optimization problems in liner shipping. Research in liner shipping is motivated by a need for handling still more complex decision problems, based on big data sets and going across several organizational entities. Moreover, liner shipping optimization problems are pushing the limits of optimization methods, creating a new breeding ground for advanced modelling and solution methods. Starting from liner shipping network design, we consider the problem of container routing and speed optimization. Next, we consider empty container repositioning and stowage planning as well as disruption management. In addition, the problem of bunker purchasing is considered in depth. In each section we give a clear problem description, bring an overview of the existing literature, and go in depth with a specific model that somehow is essential for the problem. We conclude the survey by giving an introduction to the public benchmark instances LINER-LIB. Finally, we discuss future challenges and give directions for further research.

Advanced Methods of Modelling and Design of Plate Heat Exchangers

Research of devices for heat recovery is currently focused on increasing the heat effectiveness of plate heat exchangers. The goal of optimization is not only to increase the heat transfer but also reduce the pressure loss and material costs. During the optimization of plate heat exchangers using CFD, we are struggling with the problem of how to create a quality computational mesh inside complex and irregular channels. These channels are formed by combining individual plates or blades that are shaped by molding, vacuum forming, or similar technology. Creating computational mesh from the bottom up manually is time consuming and does not help later optimization. The paper presents a new method for creating of computational meshes to simulate flow and heat transfer in a plate heat exchanger. This method is based on dynamic mesh method “user defined deforming” provided by ANSYS Fluent. The method is fast and provide applicable tool for optimization. Influences of cell size and count of layers of computational cells on heat transfer and pressure drop were investigated. It was found that the minimum number of layers is twelve across the channel, otherwise obtained data can be irrelevant.

Advanced Modeling and Simulation Methods for Multiphysics and Multiscale Problems

Advanced Modeling and Simulation Methods for Multiphysics and Multiscale Problems

An empirical comparison of four technology-mediated travel survey methods

The increasing demand for advanced modelling methods, which can reflect complex travel activities of individuals, requires enhanced travel data collection methods. The introduction of GPS-assisted data collection methods has provided an alternative to the conventional methods of travel data collection. GPS-assisted data collection methods improve the accuracy of data collection and enable capturing more details of individuals' travel behaviour. Recent technological advancements in smartphone-based positioning technologies and communication facilities have opened up new opportunities to apply smartphones as the media of GPS-assisted data collection. Although, different GPS-assisted methods have been employed recently, their performance has not been widely evaluated in real-world experiments compared to traditional data collection methods. Accordingly, this paper evaluates the performance of three GPS-assisted methods, namely handheld GPS tracking, smartphone-based GPS tracking and smartphone-based prompted-recall data collection methods, in conjunction with the web-based data collection to shed light on different aspects of GPS-assisted data collection methods. These methods are compared in terms of the quality and accuracy of the collected data, the demographic attributes of participants and the specifications of labelled trips. The results show that an appropriate employment of smartphones enhances the accuracy of data collection. It is also found that putting an extra burden on participants during a travel data collection survey results in lower trip-rates and poor data quality. Finally, it is found that the application of smartphone-assisted data collection methods help reporting non-motorised trips more accurately.

APPLICATION OF DELPHI METHOD IN CONSTRUCTION ENGINEERING AND MANAGEMENT RESEARCH: A QUANTITATIVE PERSPECTIVE

The Delphi method has been used as a main research method by a growing number of researchers in the Construction Engineering and Management (CEM) field in the past two decades. Although a number of studies are available on the use of Delphi, few researchers fully examine the potential of the Delphi method in the combined use of statistical techniques, which is an inevitable trend for future Delphi research. This paper aims to review the combined use of Delphi and other quantitative methods in the CEM field based on a structured literature review of 88 relevant papers. All of the 88 papers are systematically identified from ten well-known peer-reviewed CEM journals published in the period of 1990–2012. Topic coverage, application requirements, and statistical techniques in the 88 Delphi papers are reviewed. The mix use of the Delphi method with three advanced modelling methods, such as Fuzzy sets, Analytical Hierarchy Process, and Analytical Network Process is also examined. These review results provide practical references for researchers having interests in applying Delphi method in CEM research.

An advanced 3D modeling method for concrete-like particle-reinforced composites with high volume fraction of randomly distributed particles

An advanced numerical method is proposed to generate more realistic 3D meso-scale models for concrete-like particle-reinforced composites with high volume fraction of particles. In traditional methods, it usually consumes an excessive amount of computational time, and even worse, it cannot be realized when the volume fraction exceeds the computational limitation. A novel idea is presented in this paper in which free fall acceleration is applied to simulate the falling process of randomly distributed particles. Firstly, certain numbers of convex particles are generated based on a grading curve, and then the particles are randomly placed into a higher space than the required specimen size in height. The time for the intersection detection is significantly saved as the intersection possibility among particles in a larger space is decreased. Secondly, the surfaces of the generated particles are meshed with shell elements, and then the particles fall freely into a certain container. Finally, the matrix and particles are meshed with solid elements for further numerical analysis. Comparing with other modeling methods, this method can establish models with higher particle volume fraction. Besides, the minimum gap between adjacent particles can be flexibly controlled by changing the thickness of the shell elements. So numerical models with different volume fractions can be obtained easily. Moreover, computational cost and time can be effectively reduced. Based on this method, some numerical simulations have been carried out, and the results of numerical simulations in different loading cases all have good consistency with experimental data, which implies the accuracy of the method and the isotropy of the phase arrangements. This method is of great importance in performance analysis, structural optimization, and material design for particle-reinforced composites.

WE‐A‐201‐00: Anne and Donald Herbert Distinguished Lectureship On Modern Statistical Modeling

Chris Marshall: Memorial IntroductionDonald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”.Don developed an interest in chemistry at school by “reading a book” ‐ a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self‐taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio‐Statistics and Epidemiology Core Unit working in part on a sickle‐cell disease. After retirement he remained active as Professor Emeritus.Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co‐editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004.Don's second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us.This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own.Andrzej Niemierko:Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

WE‐A‐201‐02: Modern Statistical Modeling

Chris Marshall: Memorial IntroductionDonald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”.Don developed an interest in chemistry at school by “reading a book” ‐ a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self‐taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio‐Statistics and Epidemiology Core Unit working in part on a sickle‐cell disease. After retirement he remained active as Professor Emeritus.Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co‐editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004.Don's second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us.This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own.Andrzej Niemierko:Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

WE‐A‐201‐01: Memorial Introduction

Chris Marshall: Memorial IntroductionDonald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”.Don developed an interest in chemistry at school by “reading a book” ‐ a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self‐taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio‐Statistics and Epidemiology Core Unit working in part on a sickle‐cell disease. After retirement he remained active as Professor Emeritus.Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co‐editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004.Don's second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us.This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own.Andrzej Niemierko:Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

Design technologies for eco-industrial parks: From unit operations to processes, plants and industrial networks

The concept of eco-industrial park (EIP) has recently become the subject of a great deal of attention from industry and academic research groups. This paper proposes a series of systematic approaches for multi-level modelling and optimisation in EIPs. The novelties of this work include, (1) building a four-level modelling framework (from unit level to process level, plant level and industrial network level) for EIP research, (2) applying advanced mathematical modelling methods to describe each level operation, (3) developing efficient methodologies for solving optimisation problems at different EIP levels, (4) considering symbiotic relations amongst the three networks (material, water and energy networks) at the top EIP level with the boundary conditions of economic, social and legal requirements. For methodology demonstration, two cases at process level and industrial network level respectively are tested and solved with the developed modelling and optimisation strategies. Finally, the challenges and applications in future EIP research are also discussed, including data collection, the extension of the current networks to EIPs, and the feasibility of the proposed methodologies for complex EIP problems. The extended EIPs include the combination of material exchanges, energy systems and waste-water treatment networks. The aspects considered for future industrial ecology are carbon emission, by-product reuse, water consumption, and energy consumption. The main object of this paper is to explain the detailed model construction process and the development of optimisation approaches for a complex EIP system. In future work, this system is expected to share services, utility, and product resources amongst industrial plants to add value, reduce costs, improve environment, and consequently achieve sustainable development in a symbiosis community.

Pt-decorated In2O3 nanoparticles and their ability as a highly sensitive (

This paper reports on the high sensitivity of sub-spherical In2O3-Pt nanoparticles (NPs) for detecting ppb levels of acetone, a biomarker for diabetes. The In2O3-Pt NPs, in the form of monodisperse metal-oxide In2O3 NPs with diameters of 6–8nm, decorated with 2wt% Pt metal NPs (2–3nm) on the surface, were synthesized by a novel non-aqueous sol–gel route. NPs samples were investigated by X-ray powder diffraction (XRPD), using the advanced whole powder pattern modeling (WPPM) method, and high-resolution transmission electron microscopy (HR-TEM). The advantage of this preparative process is that it preserves metallic platinum NPs formed during the synthesis. The highly sensitive acetone sensor based on these NPs, showed a lower detection limit as low as 10ppb or less, which is the lowest detection limit ever reported for any chemoresistive acetone sensors. This exceptional performance is likely due to the key role played by very small Pt metal NPs uniformly distributed in the In2O3-Pt nanostructure. The developed sensor would be suitable for use as a highly sensitive, practical breath acetone checker for daily diet and diabetes management and diagnosis.

Mathematical Modeling Formation of 7-hydroxymethotrexate from Methotrexate in Patients Undergoing Treatment for Psoriasis with Methotrexate

Objective: To provide a further example showing a successful use of an advanced mathematical modeling method based on the theory of dynamic systems in pharmacokinetics. Method: The use of the method considered here was exemplified by modeling the formation of 7-hydroxymethotrexate (7OH-MTX) from methotrexate (MTX) in patients undergoing treatment for psoriasis with MTX. Results: The metabolic ratios of MTX to 7OH-MTX in plasma were constant during the first three months of the treatment of the patients for psoriasis. However, the mean time of formation of 7OH-MTX from MTX increased from 9.35 h to 15.59 h, and the rate of the formation of 7OH-MTX from MTX decreased from 0.5 l/h to 0.29 l/h during the same time interval. Conclusions: The advanced mathematical modeling method used in the current study is universal. Therefore, it can be used to develop mathematical models not only in pharmacokinetics but also in several scientific and practical fields.

Inverse analysis of cyclic constitutive models for unsaturated soil under consideration of oscillating functions

In order to assess the probability of foundation failure resulting from cyclic action on structures and to minimize the prediction error, various existing constitutive models considering cyclic loaded dry soils were extended to unsaturated soil conditions by the authors, thus requiring further calibration during application on existing slightly variable soil condition as well as the soil heterogeneities. The efficiency and effectiveness of these models is majorly influenced by the cyclic constitutive parameters and the soil suction. Little or no details exist in literature about the model based identification and the calibration of the constitutive parameters under cyclic loaded soils. This could be attributed to the difficulties and complexities of the inverse modeling of such complex phenomena. A wide variety of optimization strategies for the solution of the sum of least-squares problems as usually done in the field of model calibration exists, however the inverse analysis of the unsaturated soil response under oscillatory load functions has not been solved up to now. This paper gives insight into the model calibration challenges and also puts forward advanced optimization methods for the inverse modeling of cyclic loaded foundation response on unsaturated soils.

Light-Induced Degradation of Thin Film Silicon Solar Cells

Silicon-wafer based solar cells are still domination the market for photovoltaic energy conversion. However, most of the silicon is used only for mechanical stability, while only a small percentage of the material is needed for the light absorption. Thin film silicon technology reduces the material demand to just some hundred nanometer thickness. But even in a tandem stack (amorphous and microcrystalline silicon) the efficiencies are lower, and light-induced degradation is an important issue. The established standard tests for characterisation are not precise enough to predict the performance of thin film silicon solar cells under real conditions, since many factors do have an influence on the degradation. We will show some results of laboratory and outdoor measurements that we are going to use as a base for advanced modelling and simulation methods.

An efficient rotational matrix extraction scheme for finite element method-based deformation

With the development of computer science and mechanical engineering, advanced and stable soft tissue deformation modelling methods have been employed, such as mass-spring model, finite element method and meshless method. The co-rotational finite element method (co-rotational FEM), which was first introduced in physics-based computer animations, has shown its strengths to be a feasible approach to modelling the process of soft tissue deformation in a virtual surgery simulation system. In this study, we mainly investigated the method of extracting the rotational matrix which is used to perform stiffness warping assembly at each simulation time step. We first introduced and compared the time-consuming polar decomposition method and the efficient QR decomposition method, and then our hybrid rotational matrix extraction method is described. The final experimental results show that our efficient rotational matrix extraction method can improve the computation efficiency greatly without deformation accuracy losing.

Model Based Description of the Pharmacokinetic Behavior of Pentobarbital in Fasted Male Volunteers after Oral Administration of 10 mg of Pentobarbital

The goal of the current study was to present a further example which showed a model based description of the pharmacokinetic behavior of pentobarbital in fasted male volunteers after oral administration of 10 mg pentobarbital. The current study is a companion piece of the earlier study by Smith et al.; therefore the data published in the study cited here were used. For modeling purposes, an advanced modeling method based on the theory of dynamic systems was employed. All mathematical models developed, more or less successfully described the data of healthy male volunteers after oral administration of capsules containing 50 mg of sodium pentobarbital. The modeling method used in the current study is universal and uniform. Therefore, it can be used to develop mathematical models not only in pharmacokinetics but also in several other scientific and practical fields. This modeling method could augment, or in future replace, a variety of different modeling methods traditionally used in pharmacokinetics.

Building the “Triple R” in global manufacturing

Responsiveness, robustness and resilience (the “Triple R”) have become key objectives in global manufacturing, as a way of gaining competitive advantage in the global marketplace. The goal is to hedge against business uncertainties, so as to maximize the robustness of operations, maximize responsiveness by generating operational flexibility at the minimum cost, use of inventories and environmental impact, and to build resilience in global manufacturing, in order to achieve strategic flexibility. The Triple R is achieved by integrating major operational items, including planning, scheduling, real-time optimization and control. This article reviews existing contributions in the field of global manufacturing, and synthesizes these into a single conceptual model of Triple R. The overview is provided in terms of the development of decision support tools and methods, particularly the development of mathematical programming. The review reveals the fact that there have been limited contributions on the social side of sustainability. Environmental impact can be assessed by considering the product life cycle, yet the integration of R&D into global manufacturing operations has received limited contributions. On the modelling side, there are three dominant approaches: transfer pricing, strategic sourcing strategy, and logistics networks design. The paper ends by presenting a conceptual model and providing a methodological procedure for building the Triple R in global manufacturing. We also suggest implementing more advanced modelling and solution methods, which cover not only logistics and transports, but also the integration of concurrent engineering (CE) with aggregate production planning and scheduling.

High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes.

Despite the widespread use of kinase-targeted agents in clear cell renal cell carcinoma (CC-RCC), comprehensive kinase activity evaluation (kinomic profiling) of these tumors is lacking. Thus, kinomic profiling of CC-RCC may assist in devising a classification system associated with clinical outcomes, and help identify potential therapeutic targets. Fresh frozen CC-RCC tumor lysates from 41 clinically annotated patients who had localized disease at diagnosis were kinomically profiled using the PamStation®12 high-content phospho-peptide substrate microarray system (PamGene International). Twelve of these patients also had matched normal kidneys available that were also profiled. Unsupervised hierarchical clustering and supervised comparisons based on tumor vs. normal kidney and clinical outcome (tumor recurrence) were performed and coupled with advanced network modeling and upstream kinase prediction methods. Unsupervised clustering analysis of localized CC-RCC tumors identified 3 major kinomic groups associated with inflammation (A), translation initiation (B), and immune response and cell adhesions (C) processes. Potential driver kinases implicated include PFTAIRE (PFTK1), PKG1, and SRC, which were identified in groups A, B, and C, respectively. Of the 9 patients who had tumor recurrence, only one was found in Group B. Supervised analysis showed decreased kinase activity of CDK1 and RSK1-4 substrates in those which progressed compared to others. Twelve tumors with matching normal renal tissue implicated increased PIM’s and MAPKAPK’s in tumors compared to adjacent normal renal tissue. As such, comprehensive kinase profiling of CC-RCC tumors could provide a functional classification strategy for patients with localized disease and identify potential therapeutic targets.