SimTech Publications

Abstract

Neck movement and injury during a car crash is influenced by reflexes, strength, and flexibility. This data set contains in-vivo measurements of neck kinematics and reflexes as participants are rapidly accelerated while driving a mechanically simulated car. This data set includes measurements from a mechanical driving simulator that has a limited range of movement on the order of 10’s of centimeters (ITM). Torso, head and neck kinematics are measured using infrared reflective markers and cameras while electrical activity from the neck muscles are recorded using surface electromyography. MVC tests for flexion and extension are used to normalize the EMG signals.

Abstract

Nowadays, active human body models are becoming essential tools for the development of integrated occupant safety systems. However, their broad application in industry and research is limited due to the complexity of incorporated muscle controllers, the long simulation runtime, and the non-regular use of physiological motor control approaches. The purpose of this study is to address the challenges in all indicated directions by implementing a muscle controller with several physiologically inspired control strategies into an open-source extended Hill-type muscle model formulated as LS-DYNA user-defined umat41 subroutine written in the Fortran programming language. This results in increased usability, runtime performance and physiological accuracy compared to the standard muscle material existing in LS-DYNA. The proposed controller code is verified with extensive experimental data that include findings for arm muscles, the cervical spine region, and the whole body. Selected verification experiments cover three different muscle activation situations: (1) passive state, (2) open-loop and closed-loop muscle activation, and (3) reflexive behaviour. Two whole body finite element models, the 50th percentile female VIVA OpenHBM and the 50th percentile male THUMS v5, are used for simulations, complemented by the simplified arm model extracted from the 50th percentile male THUMS v3. The obtained results are evaluated additionally with the CORrelation and Analysis methodology and the mean squared error method, showing good to excellent biofidelity and sufficient agreement with the experimental data. It was shown additionally how the integrated controller allows simplified mimicking of the movements for similar musculoskeletal models using the parameters transfer method. Furthermore, the Hill-type muscle model presented in this paper shows better kinematic behaviour even in the passive case compared to the existing one in LS-DYNA due to its improved damping and elastic properties. These findings provide a solid evidence base motivating the application of the enhanced muscle material with the internal controller in future studies with Active Human Body Models under different loading conditions.

Abstract

Abstract Significant trends in the vehicle industry are autonomous driving, micromobility, electrification and the increased use of shared mobility solutions. These new vehicle automation and mobility classes lead to a larger number of occupant positions, interiors and load directions. As safety systems interact with and protect occupants, it is essential to place the human, with its variability and vulnerability, at the center of the design and operation of these systems. Digital human body models (HBMs) can help meet these requirements and are therefore increasingly being integrated into the development of new vehicle models. This contribution provides an overview of current HBMs and their applications in vehicle safety in different driving modes. The authors briefly introduce the underlying mathematical methods and present a selection of HBMs to the reader. An overview table with guideline values for simulation times, common applications and available variants of the models is provided. To provide insight into the broad application of HBMs, the authors present three case studies in the field of vehicle safety: (i) in-crash finite element simulations and injuries of riders on a motorcycle; (ii) scenario-based assessment of the active pre-crash behavior of occupants with the Madymo multibody HBM; (iii) prediction of human behavior in a take-over scenario using the EMMA model.

Abstract

The subject of this paper is a generalized Camassa–Holm equation under random perturbation. We first establish local existence and uniqueness results as well as blow-up criteria for pathwise solutions in the Sobolev spaces Hs with s>3/2. Then we analyze how noise affects the dependence of solutions on initial data. Even though the noise has some already known regularization effects, much less is known concerning the dependence on initial data. As a new concept we introduce the notion of stability of exiting times and construct an example showing that multiplicative noise (in Itô sense) cannot improve the stability of the exiting time, and simultaneously improve the continuity of the dependence on initial data. Finally, we obtain global existence theorems and estimate associated probabilities.

Abstract

The present work aims at the identification of the effective constitutive behavior of �5 aluminum grain boundaries (GB) for proportional loading by using machine learning (ML) techniques. The input for the ML approach is high accuracy data gathered in challenging molecular dynamics (MD) simulations at the atomic scale for varying temperatures and loading conditions. The effective traction-separation relation is recorded during the MD simulations. The raw MD data then serves for the training of an artificial neural network (ANN) as a surrogate model of the constitutive behavior at the grain boundary. Despite the extremely fluctuating nature of the MD data and its inhomogeneous distribution in the traction-separation space, the ANN surrogate trained on the raw MD data shows a very good agreement in the average behavior without any data-smoothing or pre-processing. Further, it is shown that the trained traction-separation ANN captures important physical properties and is able to predict traction values for given separations not contained in the training data. For example, MD simulations show a transition in traction-separation behaviour from pure sliding mode under shear load to combined GB sliding and decohesion with intermediate hardening regime at mixed load directions. These changes in GB behaviour are fully captured in the ANN predictions. Furthermore, by construction, the ANN surrogate is differentiable for arbitrary separation and also temperature, such that a thermo-mechanical tangent stiffness operator can always be evaluated. The trained ANN can then serve for large-scale FE simulation as an alternative to direct MD-FE coupling which is often infeasible in practical applications.

Abstract

A variety of methods is available to quantify uncertainties arising within the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough comparisons. Usually, raw data from such storage sites can hardly be described by theoretical statistical distributions since only very limited data is available. Hence, exact information on distribution shapes for all uncertain parameters is very rare in realistic applications. We discuss and compare four different methods tested for data-driven uncertainty quantification based on a benchmark scenario of carbon dioxide storage. In the benchmark, for which we provide data and code, carbon dioxide is injected into a saline aquifer modeled by the nonlinear capillarity-free fractional flow formulation for two incompressible fluid phases, namely carbon dioxide and brine. To cover different aspects of uncertainty quantification, we incorporate various sources of uncertainty such as uncertainty of boundary conditions, of parameters in constitutive relations, and of material properties. We consider recent versions of the following non-intrusive and intrusive uncertainty quantification methods: arbitrary polynomial chaos, spatially adaptive sparse grids, kernel-based greedy interpolation, and hybrid stochastic Galerkin. The performance of each approach is demonstrated assessing expectation value and standard deviation of the carbon dioxide saturation against a reference statistic based on Monte Carlo sampling. We compare the convergence of all methods reporting on accuracy with respect to the number of model runs and resolution. Finally, we offer suggestions about the methods' advantages and disadvantages that can guide the modeler for uncertainty quantification in carbon dioxide storage and beyond.

Abstract

A variety of methods is available to quantify uncertainties arising within the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough comparisons. Usually, raw data from such storage sites can hardly be described by theoretical statistical distributions since only very limited data is available. Hence, exact information on distribution shapes for all uncertain parameters is very rare in realistic applications. We discuss and compare four different methods tested for data-driven uncertainty quantification based on a benchmark scenario of carbon dioxide storage. In the benchmark, for which we provide data and code, carbon dioxide is injected into a saline aquifer modeled by the nonlinear capillarity-free fractional flow formulation for two incompressible fluid phases, namely carbon dioxide and brine. To cover different aspects of uncertainty quantification, we incorporate various sources of uncertainty such as uncertainty of boundary conditions, of parameters in constitutive relations, and of material properties. We consider recent versions of the following non-intrusive and intrusive uncertainty quantification methods: arbitrary polynomial chaos, spatially adaptive sparse grids, kernel-based greedy interpolation, and hybrid stochastic Galerkin. The performance of each approach is demonstrated assessing expectation value and standard deviation of the carbon dioxide saturation against a reference statistic based on Monte Carlo sampling. We compare the convergence of all methods reporting on accuracy with respect to the number of model runs and resolution. Finally, we offer suggestions about the methods’ advantages and disadvantages that can guide the modeler for uncertainty quantification in carbon dioxide storage and beyond.

Abstract

We present a hybrid-dimensional numerical model for non-isothermal two-phase flow in fractured porous media, in which the fractures are modeled as entities of codimension one embedded in a bulk domain. Potential fields of applications of the model could be radioactive waste disposal or geothermal energy production scenarios in which a two-phase flow regime develops or where \$\$\backslashhbox \CO\\_2\$\$CO2 is used as working fluid. We test the method on synthetic test cases involving compressible fluids and strongly heterogeneous, full tensor permeability fields by comparison with a reference solution obtained from an equi-dimensional discretization of the domain. The results reveal that especially for the case of a highly conductive fracture, the results are in good agreement with the reference. While the model qualitatively captures the involved phenomena also for the case of a fracture acting as both hydraulic and capillary barrier, it introduces larger errors than in the highly-conductive fracture case, which can be attributed to the lower-dimensional treatment of the fracture. Finally, we apply the method to a three-dimensional showcase that resembles setups for the determination of upscaled parameters of fractured blocks.

Abstract

This work proposes a data-driven method for enabling the efficient, stable time-parallel numerical solution of systems of ordinary differential equations (ODEs). The method assumes that low-dimensional bases that accurately capture the time evolution of the dynamical-system state are available. The method adopts the parareal framework for time parallelism, which is defined by an initialization method, a coarse propagator that advances solutions on a coarse time grid, and a fine propagator that operates on an underlying fine time grid. Rather than employing usual approaches for initialization and coarse propagation, we propose novel data-driven techniques that leverage the available time-evolution bases. The coarse propagator is defined by a forecast (proposed in K. Carlberg, J. Ray, and B. van Bloemen Waanders, Comput. Methods Appl. Mech. Engrg., 289 (2015), pp. 79--103) applied locally within each coarse time interval, which comprises the following steps: (1) apply the fine propagator for a small number of time steps, (2) approximate the state over the entire coarse time interval using gappy proper orthogonal decomposition (POD) with the local time-evolution bases, and (3) select the approximation at the end of the time interval as the propagated state. We also propose both local-forecast and global-forecast initialization techniques. The method is particularly well suited for POD-based reduced-order models (ROMs), as the time-evolution bases can be extracted from readily available data, i.e., the right singular vectors arising during POD computation. In addition to performing analyses related to the method's accuracy, speedup, stability, and convergence, we also numerically demonstrate the method's performance. Here, numerical experiments on ROMs for a nonlinear convection--reaction problem demonstrate the method's ability to realize near-ideal speedups.

Abstract

By its very nature, research into multi-physical processes occurring in porous and fractured media requires a collaborative approach. An interdisciplinary approach has led to the adoption of collaborative software development paradigms in this field relying on software for scientific computing as research infrastructures. The development of open-source software has become a cornerstone of computational approaches in academia and has even spawned successful business models in the commercial world. This article is geared toward readers who want to learn more about potential benefits of open-source software in porous media research and who want to familiarize themselves with typical workflows required to become an active contributor to or user of open-source solutions for porous media simulation. The article puts general principles, motivations and concepts into the specific context of experiences and lessons learned from the authors developing the open-source software projects OpenGeoSys and DuMu\$\$^\\backslashtext \x\\\$\$.

Abstract

We consider feedback interconnections composed of a linear system whose input-output behavior is constrained by a relation. It is shown how to analyze stability of such interconnections by suitably refining the general framework of integral quadratic constraints. For the special case of static multivalued monotone nonlinearities, we reveal that one can employ Zames-Falb multipliers in order to substantially reduce conservatism if compared with passivity-based approaches and as illustrated with a numerical example. Our results are expected to open up an avenue towards a systematic stability analysis of data-integrated systems.

Abstract

We derive novel criteria for robust stability and output-feedback gain-scheduling controller synthesis for a class of switched systems that are affected by piecewise constant parameters with dwell-time constraints. Our findings are based on clock-dependent Lyapunov arguments and rely, in contrast to other approaches, on separation techniques from robust control involving dynamic multipliers. The obtained conditions are expressed as infinite-dimensional linear matrix inequalities which can be solved by, e.g., using sum-of-squares relaxation methods. We illustrate our results with a numerical example.

Abstract

Robust stability of a class of linear time-invariant systems affected by piecewise constant parameters with dwell-time constraints is considered. In contrast to other approaches the proposed result relies on separation techniques within the framework of integral quadratic constraints and is based on a novel version of the swapping lemma. In particular, our result allows to take additional knowledge on the variation of the parameter into account. The obtained conditions are expressed as infinite-dimensional linear matrix inequalities which can be solved, e.g., by using sum-of-squares relaxation methods. We illustrate the proposed approach with a numerical example.

Abstract

We present the results of atomistic molecular dynamics simulations with regard to specific ion effects in water, methanol and N,N-dimethylacetamide (DMAc). As a reference system, we introduce rigid and rod-like models of polyanions and polycations in combination with alkali metal cations and halide anions as counterions. Pronounced specific ion effects can be observed in terms of the individual anion and cation condensation behavior. The outcomes of our simulations thus reveal significant deviations from standard electrostatic mean-field theories. A detailed investigation of the individual energy contributions shows that ion–dipole interactions play a pivotal role in rationalizing the findings. The corresponding deviations in terms of the cation and anion distribution can be brought into agreement with the donor and acceptor numbers of the solvents, which thus highlights the importance of solvent–ion interactions in addition to electrostatic attraction.

Abstract

The numericalSchneider, Martinsimulation ofGläser, Dennissubsurface processesHelmig, Rainerrequires efficientFlemisch, Berndand robust methods due to the large scales and the complex geometries involved. In this article, a nonlinear finite-volume scheme is presented and applied to non-isothermal two-phase two-component flow in porous media. The idea of the scheme and the model used for the simulations are outlined and a comparison to a standard scheme used in industrial codes is made. Large-scale offshore CO\$\$\_2\$\$storage in the Johansen formation serves as a benchmark problem, where it is demonstrated that the new scheme can handle highly complex corner-point grids and reproduces the physical processes with a higher accuracy than the standard discretization scheme.

Abstract

We introduce a framework to synthesize block-diagonal H∞-controllers with a parametric and a block-triangular dynamic component by convex optimization. This is motivated by a recent H∞-design approach for systems with delayed interconnections that are structured according to a strongly-connected communication graph. Our framework allows the extension to synthesis for interconnections described by multiple strongly-connected graphs that are themselves coupled through a nested delay structure.

Abstract

The tumour necrosis factor (TNF) ligand family member TNF-related apoptosis-inducing ligand (TRAIL) induces apoptosis predominantly in tumour cells, but not in normal tissues, representing therefore an attractive candidate for cancer therapy. The human TRAIL/TRAIL receptor system is very complex, four different membrane receptors bind the ligand. Two of these receptors, TRAIL-R1 and TRAIL-R2, transmit apoptotic but also non-apoptotic signals, whereas the other two, TRAIL-R3 and TRAIL-R4, act as inhibitors. Most tumour cells co-express several TRAIL receptors, allowing receptor interference. Several molecular mechanisms have been proposed by which TRAIL-R3 and TRAIL-R4 may counteract pro-apoptotic TRAIL signalling at the plasma membrane level, but possibly also intracellularly. A detailed understanding of the role of the individual TRAIL receptors and their interplay will be advantageous for the development of new TRAIL receptor agonists for cancer therapy. In fact, new TRAIL formulations will be needed since first clinical studies with soluble TRAIL or receptor agonistic antibodies showed only limited success. This review summarizes the complex TRAIL/TRAIL receptor system and the mechanisms by which TRAIL-R3 and TRAIL-R4 may interfere with TRAIL-mediated apoptosis induction. In addition, we discuss the prognostic and predictive value of TRAIL receptor expression in patients' tumour material.

Abstract

The need for extended liver resection is increasing due to the growing incidence of liver tumors in ageing societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.

Abstract

We consider systems that consist of infinitely many identical subsystems over an infinite undirected graph. Stability analysis for such systems is performed and embedded into multiplier theory from robust control. This allows to apply recently developed gain-scheduling methods for dynamic multipliers in order to design stabilizing controllers and yields LMI conditions for their existence that are less conservative than existing ones.

Abstract

In this work we investigate the interplay of polynomial de-aliasing and sub-grid scale models for large eddy simulations based on discontinuous Galerkin discretizations. It is known that stability is a major concern when simulating underresolved turbulent flows with high order nodal collocation type discretizations. By changing the interpolatory character of the nodal collocation type discretization to a projection based discretization by increasing the number of quadrature points (polynomial de-aliasing), one is able to remove the aliasing induced stability problems. We focus on this effect and on the consequence for large eddy simulations with explicit subgrid scale models. Often, subgrid scale models have to achieve two possibly conflicting tasks in a single simulation: firstly stabilizing the numerics and secondly modeling the physical effect of the missing scales. Within a discontinuous Galerkin approach, it is possible to use either a fast (but potentially aliasing afflicted) nodal collocation discretization or a projection-based (but computationally costly) variant in combination with an explicit subgrid scale model. We use this framework to investigate the effect on the appropriate model parameter of a standard Smagorinsky subgrid scale model and of a Variational Multiscale Smagorinsky formulation. For this we first consider the 3-D viscous Taylor-Green vortex example to investigate the impact on the stability of the method and second the turbulent flow past a circular cylinder to investigate and compare the accuracy of the results. We show that the aliasing instabilities of collocative discretizations severely limit the choice of the model constant, in particular for high order schemes, while for de-aliased DG schemes, the closure model parameters can be chosen independently from the numerical scheme. For the cylinder flow, we also find that for the same model settings, the projection-based results are in better agreement with the reference DNS than those of the collocative scheme.

Abstract

This study focuses on a two-scale, continuum multicomponent model for the description of blood perfusion and cell metabolism in the liver. The model accounts for a spatial and time depending hydro-diffusion--advection--reaction description. We consider a solid-phase (tissue) containing glycogen and a fluid-phase (blood) containing glucose as well as lactate. The five-component model is enhanced by a two-scale approach including a macroscale (sinusoidal level) and a microscale (cell level). The perfusion on the macroscale within the lobules is described by a homogenized multiphasic approach based on the theory of porous media (mixture theory combined with the concept of volume fraction). On macro level, we recall the basic mixture model, the governing equations as well as the constitutive framework including the solid (tissue) stress, blood pressure and solutes chemical potential. In view of the transport phenomena, we discuss the blood flow including transverse isotropic permeability, as well as the transport of solute concentrations including diffusion and advection. The continuum multicomponent model on the macroscale finally leads to a coupled system of partial differential equations (PDE). In contrast, the hepatic metabolism on the microscale (cell level) was modeled via a coupled system of ordinary differential equations (ODE). Again, we recall the constitutive relations for cell metabolism level. A finite element implementation of this framework is used to provide an illustrative example, describing the spatial and time-depending perfusion--metabolism processes in liver lobules that integrates perfusion and metabolism of the liver.

Abstract

We present the numerical implementation of a model that couples single-phase free and two-phase porous-media flow and transport with the focus on the treatment of the interface conditions. The model concept is based on the two-domain approach and on non-isothermal compositional submodels. These are coupled by interface conditions accounting for mass, momentum and energy transfer, and guaranteeing continuity of fluxes. A vertex-centred finite-volume scheme is used throughout the domain and a global matrix is solved for the whole system incorporating the coupling matrices. The fluxes at the interface are calculated indirectly via a flux balance from the adjacent finite-volume boxes. Numerical examples, representing evaporation from partially saturated porous media influenced by an ambient air flow, illustrate the evolution of saturation and temperature in a reference case and demonstrate the coupling concept. Furthermore, the effect of temperature, Beavers–Joseph coefficient and permeability on the evaporation process are examined with a series of simulations. In the presented set-ups, the choice of the Beavers–Joseph coefficient has a negligible influence on the evaporation rate across the interface.

Abstract

In this work, we present the first molecular dynamics simulation on the formation of a polyelectrolyte bilayer resolved in atomistic detail, extending a previous study of the adsorption of poly(styrene sulfonate) B. Qiao, J. J. Cerda and C. Holm, Macromolecules, 2011, 44, 1707-1718. to the formation of a poly(styrene sulfonate)/poly(diallyldimethylammonium) bilayer. Extensive molecular dynamics simulations of the adsorption process on different substrates (hydrophilic/hydrophobic, charged/neutral) were performed. Our results seem to indicate that a high enough surface charge density (0.164 C m-2 here) may be required to achieve a multilayer linear growth in the framework of the electrostatic driven mechanism for PEM growth. We furthermore demonstrate that the use of stiff hydroxyl groups for creating a hydrophilic surface from a hydrophilic one can lead to severe simulation artifacts, and we discuss a simple remedy for this problem.

Abstract

A tele-haptic system for microassembly applications is currently being developed at the Delft University of Technology, with the goal of achieving superior performance by providing enhanced feedback to the human operator. Assembly of a micro-harmonic drive is used as a benchmark to fully evaluate the proposed tele-haptic system by investigating the control strategies and the individual subsystems: master device, microgrippers and slave system. The master device will be comprised of a parallel robot with a built-in gripper. The slave system and end effector are focused on providing efficient and effective force feedback of the interactions on the microenvironment to the human operator, in addition to detecting position and orientation of the object being grasped. Novel control strategies are also investigated to allow the transmission of high frequency transients to the operator, carrying information from hard contact interactions between the microgripper and the part to be assembled.

Abstract

The nature of the missile interception problem with two noncooperative players leads to the field of differential games Introducing nonlinear uncertain models can potentially lead to nonexistence of game theoretic equilibrium strategies, computationally intractable problems, and/or highly reduced performance of the strategies The objective is therefore to obtain robust strategies that provide an upper bound on the performance of the nonlinear system against all allowable disturbances and model uncertainties Robust programming and more specific robust linear matrix inequality techniques have proved to be an extremely effective tool to design such robust control strategies This paper extends the existing robust disturbance feedback framework such that it can effectively deal with a large class of model mismatches and uncertainties such as target maneuvers and nonlinearities The implementation of these strategies in a receding horizon fashion on missile intercept problems leads to very satisfactory results when compared to traditional guidance laws

Abstract

Liver resection can lead to focal outflow obstruction due to transection of hepatic veins. Outflow obstruction may cause additional damage to the small remnant liver. Drainage of the obstructed territories is reestablished via dilatation of sinusoids. Subsequently, sinusoidal canals are formed draining the blood from the obstructed territory to the neighboring unobstructed territories. We raised the phenomenological hypothesis that the blood pressure gradient is the main driving force for the formation of sinusoidal vascular canals. We generated a biphasic mechanical model to describe this vascular remodeling process in relation to the variable pressure gradient. Therefore, we introduced a transverse isotropic permeability relation as well as an evolutional optimization rule to describe the relationship between pressure gradient and the direction of the sinusoidal blood flow in the fluid phase. As a next step, we developed a framework for the calculation concept including the representation of the governing weak formulations. Then, we examined a representative numerical example with simulation of the blood flow under both conditions, the physiological situation as well as after outflow obstruction. Doing so, we were able to reproduce numerically the experimentally observed process of reestablishing hepatic venous drainage via redirection of blood flow and formation of new vascular structures in respect to the fluid flow. The calculated results support the hypothesis that the reorientation of blood flow mainly depends on the pressure gradient. Further investigations are needed to determine the micromechanical influences on the reorientation of the sinusoids.

Abstract

Motivated by a robust disturbance rejection problem, in which disturbances are described by an uncertain filter at the plant input, a convex solution is presented for the robust output feedback controller synthesis problem for a particularly structured plant. The uncertainties are characterized by an integral quadratic constraint (IQC) with general frequency-dependent multipliers. By exploiting the structure of the generalized plant, linear matrix inequality (LMI)-synthesis conditions are derived in order to guarantee a specified L(2)-gain or H(2)-norm performance level, provided that the IQC multipliers are described by LMI constraints. Moreover, it is shown that part of the controller variables can be eliminated. Finally, the rejection of non-stationary sinusoidal disturbance signals is considered. In a numerical example, it is shown that specifying a bound on the rate-of-variation of the time-varying frequency can improve the performance if compared with the static IQC multipliers. Copyright (C) 2009 John Wiley & Sons, Ltd.

Abstract

We consider the problem of robust L(2)-gain disturbance feedforward control for uncertain systems described in the standard LFT form. We use integral quadratic constraints (IQCs) for describing the uncertainty blocks in the system. For technical reasons related to the feedforward problem, throughout the paper, we work with the duals of the constraints involved in robustness analysis using IQCs. We obtain a convex solution to the problem using a state-space characterization of nominal stability that we have developed recently. Specifically, our solution consists of LMI conditions for the existence of a feedforward controller that guarantees a given L(2)-gain for the closed-loop system. We demonstrate the effectiveness of using dynamic IQCs in robust feedforward design through a numerical example. Copyright (C) 2008 John Wiley & Sons, Ltd.