I. Kryven, Bond percolation in coloured and multiplex networks, Nature Communications 10, 404, 2019,
Percolation in complex networks is a process that mimics network degradation and a tool that reveals peculiarities of the network structure. During the course of percolation, the emergent properties of networks undergo non-trivial transformations, which include a phase transition in the connectivity, and in some special cases, multiple phase transitions. Such global transformations are caused by only subtle changes in the degree distribution, which locally describe the network. Here we establish a generic analytic theory that describes how structure and sizes of all connected components in the network are affected by simple and colour-dependent bond percolations. This theory predicts locations of the phase transitions, existence of wide critical regimes that do not vanish in the thermodynamic limit, and a phenomenon of colour switching in small components. These results may be used to design percolation-like processes, optimise network response to percolation, and detect subtle signals preceding network collapse.
V. Schamboeck, P. Iedema, I. Kryven. Dynamic Networks that Drive the Process of Irreversible Step-Growth Polymerization, Scientific Reports, 2019,
Many research fields, reaching from social networks and epidemiology to biology and physics, have experienced great advance from recent developments in random graphs and network theory. In this paper we propose to view percolation on a directed random graph as a generic model for step-growth polymerisation. This polymerisation process is used to manufacture a broad range of polymeric materials, including: polyesters, polyurethanes, polyamides, and many others. We link features of step-growth polymerisation to the properties of the directed configuration model, and in this way, obtain new analytical expressions describing the polymeric microstructure. Thus, the molecular weight distribution is related to the sizes of connected components, gelation to the emergence of the giant component, and the molecular gyration radii to the Wiener index of these components. A model on this level of generality is instrumental in accelerating the design of new materials and optimizing their properties.
I. Kryven, A.Torres-Knoop, How to Upscale The Kinetics of Complex Microsystems, 2018,
The rate constants of chemical reactions are typically inferred from slopes and intersection points of observed concentration curves. In small systems that operate far below the thermodynamic limit, these concentration profiles become stochastic and such an inference is less straightforward. By using elements of queuing theory, we introduce a procedure for inferring (time dependent) kinetic parameters from microscopic observations that are given by molecular simulations of many simultaneously reacting species. We demonstrate that with this procedure it is possible to assimilate the results of molecular simulations in such a way that the latter become descriptive on the macroscopic scale. As an example, we upscale the kinetics of a molecular dynamics system that forms a complex molecular network. Incidentally, we report that the kinetic parameters of this system feature a peculiar time and temperature dependences, whereas the probability of a network strand to close a cycle follows a universal distribution.
I. Kryven. Analytic results on the polymerisation random graph model, J Math Chem, 56 (1), 140-157, 2018,
The step-growth polymerisation of a mixture of arbitrary-functional
monomers is viewed as a time-continuos random graph process with degree bounds
that are not necessarily the same for different vertices. The sequence of degree bounds
acts as the only input parameter of the model. This parameter entirely defines the
timing of the phase transition. Moreover, the size distribution of connected components
features a rich temporal dynamics that includes: switching between exponential
and algebraic asymptotes and acquiring oscillations. The results regarding the phase
transition and the expected size of a connected component are obtained in a closed
form. An exact expression for the size distribution is resolved up to the convolution
power and is computable in subquadratic time. The theoretical results are illustrated
on a few special cases, including a comparison with Monte Carlo simulations.
I. Kryven, Colour-dependent percolation, Complex Networks & Their Applications, 406-408, 2018,
A Torres-Knoop, I Kryven, V Schamboeck, PD Iedema.
Modeling the free-radical polymerization of hexanediol diacrylate (HDDA): a molecular dynamics and graph theory approa
Soft matter 14 (17), 3404-3414, 2018
In the printing, coating and ink industries, photocurable systems are becoming increasingly popular and multi-functional acrylates are one of the most commonly used monomers due to their high reactivity (fast curing). In this paper, we use molecular dynamics and graph theory tools to investigate the thermo-mechanical properties and topology of hexanediol diacrylate (HDDA) polymer networks. The gel point was determined as the point where a giant component was formed. For the conditions of our simulations, we found the gel point to be around 0.18 bond conversion. A detailed analysis of the network topology showed, unexpectedly, that the flexibility of the HDDA molecules plays an important role in increasing the conversion of double bonds, while delaying the gel point. This is due to a back-biting type of reaction mechanism that promotes the formation of small cycles. The glass transition temperature for several degrees of curing was obtained from the change in the thermal expansion coefficient. For a bond conversion close to experimental values we obtained a glass transition temperature around 400 K. For the same bond conversion we estimate a Young's modulus of 3 GPa. Both of these values are in good agreement with experiments.
Y Orlova, I Kryven, PD Iedema.
Automated reaction generation for polymer networks,
Computers & Chemical Engineering, 112, 37-47, 2018
Most of the theoretical studies on polymer kinetics has been performed by manually reducing the chemical system to a few simple reaction mechanisms having a repeatable nature. Not being constrained by such reducibility, this work considers the polymerization as a product of a complex network of reactions that need not to be known in advance. Combining various ideas from graph theory, combinatorics and random graphs, we introduce a new modeling approach to complex polymerization that automatically constructs a reaction network, solves kinetic model, and retrieves such topological properties of the final polymer network as, for instance, distribution of molecular weight. In this way, the new approach acts as an intermediate layer that propagates the knowledge of the basic chemistry in order to capture and understand the complexity of the real world polymerizing systems.
K. Bisewski, B.M. de Leeuw, B. Kamphorst, H. Kraaijevanger, I. Kryven, J. Kuhn, A. Montefusco, M. Muskulus, T. Nesti, Y. Orlova, M. Peletier.
Quiescent Periods during Helicopter Landings on Ships,
SWI 2017 Proceedings, 52-96
The problem of helicopter landing on ships has been recently studied by MARIN (MAritime Research Institute Netherlands) with the purpose of helping the naval crew, and in particular the HLO (Helicopter Landing Officer), to take decisions in a fast and reliable way. The basic issue consisted in the prediction of time intervals, called quiescent periods (QPs), where the ship motion is sufficiently moderate for the helicopter to be able to land in safe conditions. The ingredients at our disposal were a set of wave data that were simulated by MARIN with their proprietary software FREDYN. Our first goal, then, was to study the statistics of QPs and to identify patterns. The second objective was to use the same data to make predictions on the basis of a few deterministic and stochastic models. The results show that these models are indeed able to capture several features of the waves, such as repetitions of special patterns and memory effects, and surely deserve further investigation and extension. The last approach was purely analytical: first we focus on the question whether a given sum of n harmonics will have QPs or not. After analyzing the cases n = 1,2,3 in full detail we present a general criterion for the existence of QPs for the case of arbitrary n. We also give estimates for the frequency and probability of QPs in a signal composed of many random harmonics.
I. Kryven. Finite connected components in infinite directed and multiplex networks with arbitrary degree distributions, Physical Review E 96 (5), 052304, 2017
This work presents exact expressions for size distributions of weak and multilayer connected components in two generalizations of the configuration model: networks with directed edges and multiplex networks with an arbitrary number of layers. The expressions are computable in a polynomial time and, under some restrictions, are tractable from the asymptotic theory point of view. If first partial moments of the degree distribution are finite, the size distribution for two-layer connected components in multiplex networks exhibits an exponent -3/2
in the critical regime, whereas the size distribution of weakly connected components in directed networks exhibits two critical exponents
−1/2 and −3/2.
I Kryven, YR Zhao, KB McAuley, P Iedema.
A Deterministic Model for Positional Gradients in Copolymers,
Chemical Engineering Science 177 (23), 491–500, 2018,
A deterministic modelling approach is developed to predict the internal structure of gradient copolymer chains. A key innovation of the modelling approach is the introduction of a positional variable that gives direct access to quantitative gradient characteristics: the ensemble average composition and the gradient deviation. This positional variable is used to develop multi-dimensional population balance equations that can be solved numerically to calculate gradient quality measures. The methodology is illustrated using the gradient copolymerisation of ethylene and 1-octene via coordinative chain transfer mechanism, which is representative of a variety of polymerisation schemes for gradient copolymers. Simulation results are validated with those obtained by stochastic simulations which, until now, were the only means of predicting detailed gradient quality.
V. Schamboeck, I. Kryven, P. Iedema. Acrylate Network Formation by Free-Radical Polymerization Modeled Using Random Graphs, Macromolecular Theory and Simulations, 26 (6), 1700047, 2017,
A novel technique is developed to predict the evolving topology of a diacrylate
polymer network under photocuring conditions, covering the low-viscous
initial state to full transition into polymer gel. The model is based on a new
graph theoretical concept being introduced in the framework of population
balance equations (PBEs) for monomer states (mPBEs). A trivariate degree
distribution that describes the topology of the network locally is obtained
from the mPBE, which serves as an input for a directional random graph
model. Thus, access is granted to global properties of the acrylate network
which include molecular size distribution, distributions of molecules with a
specific number of crosslinks/radicals, gelation time/conversion, and gel/sol
weight fraction. Furthermore, an analytic criterion for gelation is derived. This
criterion connects weight fractions of converted monomers and the transition
into the gel regime. Valid results in both sol and gel regimes are obtained by
the new model, which is confirmed by a comparison with a “classical” macromolecular
PBE model. The model predicts full transition of polymer into gel at
very low vinyl conversion. Typically, this low-conversion network is very
sparse, as becomes apparent from the predicted crosslink distribution.
I. Kryven. Analytical expression for the size distribution of connected components in the infinite configuration model, Complex Networks & Their Applications 6, 220-223
In the configuration network, N nodes are assigned predefined degrees. The edges connecting these nodes are then considered to be random, and every distinct configuration of edges that satisfies the given degree sequence is treated as a new instance of the network in the sense of random graphs. When the number of nodes N approaches infinity, the degree sequence, which provides the only input information for the model, is equivalent to the frequency distribution of degrees, u(k), k= 1, 2,..., i.e., the probability that a randomly chosen node has degree k. Size distribution of connected components, w(n), denotes probability that a randomly chosen node is part of a connected component of finite size n. Connected components in the infinite configuration network can be of finite or infinite size. Depending upon a specific context behind the network, the size distribution of connected components may summarise important features of the modelled system, for instance as it often happens in chemistry, where connected components represent irregular molecular structures; epidemiology, where configuration model is widely used in modelling disease outbreaks; or linguistics, where connected components are proved to be useful when studying sentence similarity graphs and structure of natural languages. This brief list of application case studies is far from being exhaustive.
I. Kryven. General expression for component-size distribution in infinite configuration networks, Physical Review E 95, 052303, 2017
In the infinite configuration network the links between nodes are assigned randomly with the only restriction that the degree distribution has to match a predefined function. This work presents a simple equation that gives for an arbitrary degree distribution the corresponding size distribution of connected components. This equation is suitable for fast and stable numerical computations up to the machine precision. The analytical analysis reveals that the asymptote of the component size distribution is completely defined by only a few parameters of the degree distribution: the first three moments, scale, and exponent (if applicable). When the degree distribution features a heavy tail, multiple asymptotic modes are observed in the component size distribution that, in turn, may or may not feature a heavy tail.
I. Kryven. Emergence of the giant weak-component in directed random graphs with arbitrary degree distributions, Physical Review, E 94, 012315, 2016
The weak component generalizes the idea of connected components to directed graphs. In this paper, an exact
criterion for the existence of the giant weak component is derived for directed graphs with arbitrary bivariate
degree distributions. In addition, we consider a random process for evolving directed graphs with bounded
degrees. The bounds are not the same for different vertices but satisfy a predefined distribution. The analytic
expression obtained for the evolving degree distribution is then combined with the weak-component criterion to
obtain the exact time of the phase transition. The phase-transition time is obtained as a function of the distribution
that bounds the degrees. Remarkably, when viewed from the step-polymerization formalism, the new results
yield Flory-Stockmayer gelation theory and generalize it to a broader scope.
I. Kryven, J. Duivenvoorden, J. Hermans, P. Iedema. Random graph approach to multifunctional molecular networks, Macromolecular Theory and Simulations 25 (5), 2016, 449--465.
Formation of a molecular network from multifunctional precursors is modelled with a random graph process. The process does not account for spatial positions of the monomers explicitly, yet the Euclidean distances between the monomers are derived from the topological information by applying self-avoiding random walks. This allows favoring reactivity of monomers that are close to each other, and to disfavor the reactivity for monomers obscured by the surrounding. As a result, the model is applicable to large time scales. The phenomena of conversion-dependent reaction rates, gelation, microgelation, and structural inhomogeneity are predicted by the model. Resulting nonhomogeneous network topologies are analyzed to extract such descriptors as: size distribution, crosslink distances, and gel-point conversion. Furthermore, new to the molecular simulation community descriptors are suggested that are especially useful when explaining evolution of the gel as being a single molecule: local clustering coefficient, network modularity, cluster size distribution.
I. Kryven, S. Rüoblitz, Ch. Schütte.
Solution of the chemical master equation by
radial basis functions approximation with
BMC System Biology 2015
Background: The chemical master equation is the fundamental equation of
stochastic chemical kinetics. This differential-difference equation describes
temporal evolution of the probability density function for states of a chemical
system. A state of the system, usually encoded as a vector, represents the
number of entities or copy numbers of interacting species, which are changing
according to a list of possible reactions. It is often the case, especially when the
state vector is high-dimensional, that the number of possible states the system
may occupy is too large to be handled computationally. One way to get around
this problem is to consider only those states that are associated with probabilities
that are greater than a certain threshold level.
I. Kryven, PD. Iedema.
Deterministic modelling of copolymer microstructure: composition drift and sequence patterns,
Results: We introduce an algorithm that significantly reduces computational
resources and is especially powerful when dealing with multi-modal distributions.
The algorithm is built according to two key principles. Firstly, when performing
time integration, the algorithm keeps track of the subset of states with significant
probabilities (essential support). Secondly, the probability distribution that solves
the equation is parametrised with a small number of coefficients using collocation
on Gaussian radial basis functions. The system of basis functions is chosen in
such a way that the solution is approximated only on the essential support instead
of the whole state space. In order to demonstrate the effectiveness of the method,
we consider four application examples: a) the self-regulating gene model, b) the
2-dimensional bistable toggle switch, c) a generalisation of the bistable switch to
a 3-dimensional tristable problem, and d) a 3-dimensional cell differentiation
model that, depending on parameter values, may operate in bistable or tristable
modes. In all multidimensional examples the manifold containing the system
states with significant probabilities undergoes drastic transformations over time.
This fact makes the examples especially challenging for numerical methods.
Conclusions: The proposed method is a new numerical approach permitting to
approximately solve a wide range of problems that have been hard to tackle until
now. A full representation of multi-dimensional distributions is recovered. The
method is especially attractive when dealing with models
Macromolecular Reaction Engineering [Special Issue: Statistical Modeling Tools and Approaches for Polymerization Reaction Engineering], Volume 9, Issue 3, pages 285–306, 2015;
A concept of a population balance is applied to study evolving structures of propagating linear copolymer chains. As a result, a general numerical toolbox was developed capable to handle various copolymerization mechanisms utilizing two-dimensional distributions as means of system description. The method was applied to free radical copolymerization of styrene–acrylonitrile explaining peculiar bimodality in chain length distribution observed for asymmetrical initial monomer ratios.
I. Kryven, PD. Iedema.
Transition into the gel regime for crosslinking radical polymerisation in a continuously stirred tank reactor,
Chemical Engineering Science, Volume 126, Issue 14, Pages 296–308, 2015
Crosslinking radical polymerisation in a continuously stirred tank reactor has been studied by means of a four-dimensional population balance model accounting for chain length, free pending double bonds, crosslinks, and multiradicals as dimensions. The model covers both pre-gel and gel regimes in a straightforward manner. Approximations on radial basis functions have been employed to reduce the size of the system with minimal information loss. The comparison with Monte Carlo simulations shows interesting and unexpected features.
A. van Dam,
B. de Leeuw,
Always Nice Weather in Europe.
Proceedings SWI 2015
Weather forecasting relies on mathematical models that exhibit chaotic behavior. This
renders the solution of these models very sensitive to errors in the model, to choices of the
initial conditions and to rounding errors in the numerical solution procedure. Over the course
of the past decade, various meteorological institutes in Europe have developed different at-
mosphere models. Each of these models has its strengths and weaknesses. The principle
behind the so-called Super Modeling approach is to merge these existing models into a single
larger model to combine common strengths while overcoming individual weaknesses. This
approach was initially proposed and developed by the KNMI in the Netherlands to improve
the reliability of its weather forecasts. The task formulated for this Study Group problem was
to reevaluate the Super Modeling approach and to formulate recommendations for its future
Topology evolution in macromolecular networks,
Univeristy of Amsterdam, PhD Thessis, ISBN: 978-90-9028519-1, 2014;
Governed by various intermolecular forces, molecular networks tend to evolve
from simple to very complex formations that have random structure. This
randomness in the connectivity of the basic units can still be
captured employing distributional description of the state of the system;
the evolution itself by particular stochastic processes, for instance
Smoluchowski coagulation. The Smoluchowski coagulation equation can be
extended to include collisions of orders distinct from 2, which allows
developing a framework that covers various special cases being far beyond
the scope of the original application of the coagulation equation. The
combination of the population balance equation based on a generalization of
the Smoluchowski coagulation and a meshless projection method based on
Gaussian basis functions has been found to be a powerful tool allowing to
solve many problems of prior unmanageable complexity. For instance, in the
case of cross-linking polymerisation in bulk, the population balance model
describing a particular set of reaction mechanisms has been present in
literature for decades before it has been successfully and to a full extent
solved by the numerical method. The other case studies address formation of
various molecular networks in a few important cases: polymerisation of AB2
monomers, modification of linear chains into a branched
polymer, copolymerisation with a composition drift, and coagulation/
coalescence of colloids of variable fractal dimension.
I. Kryven, PD. Iedema.
Transition into the gel regime for free radical crosslinking polymerisation in a batch reactor,
Polymer, Volume 55, Issue 16, Pages 3475–3489, 2014;
I. Kryven, S. Lazzari, G. Storti.
Population Balance Modeling of Aggregation and Coalescence in Colloidal Systems,
Crosslinking polymerization has been studied by means of a four-dimensional population balance model accounting for chain length, free pending double bonds, crosslinks, and multiradicals as dimensions. The model, for the first time and to a full extent resolves the crosslinking problem as formulated by Zhu et al. 
and covers both pre-gel and gel regimes, in a straightforward manner. Approximations on radial basis functions have been employed to reduce the size of the system with minimal information loss. The model has been validated with data from an experimental crosslinking polymerization, Methyl Methacrylate with Ethylene Glycol Dimethacrylate. Non-trivial patterns in the time evolution of average quantities like crosslink densities, partly observed in prior studies [2
], are naturally emerging from the model by computing marginals of the four-dimensional distribution possessing an interesting multimodal structure.
Macromolecular Theory and Simulations, Volume 55, Issue 16, Pages 3475–3489, 2014;
A complex interplay between aggregation and coalescence occurs in many colloidal polymeric systems and determines the morphology of the final clusters of primary particles. To describe this process, a 2D population balance equation (PBE) based on cluster mass and fractal dimension is solved, employing a discretization method based on Gaussian basis functions. To prove the general reliability of the model and to show its potential, parametric simulations are performed employing both diffusion-limited-cluster aggregation (DLCA) and reaction-limited-cluster-aggregation (RLCA) kernels and different coalescence rates. It turns out that in both DLCA and RLCA regimes, a faster coalescence leads to smaller sized and more compact clusters, whereas a slow coalescence promotes the formation of highly reactive
I. Kryven, PD. Iedema.
Topology Evolution in Polymer Modification,
Macromolecular Theory and Simulations, Volume 23, Issue 1, pages 7–14, 2014
A recent numerical method has opened new opportunities in multidimensional population balance modeling. Here, this method is applied to a full three-dimensional population balance model (PBM) describing branching topology evolution driven by chain end to backbone coupling. This process is typical for polymer modification reactions, e.g., in polyethylene, where initially linear polymer chains undergo hydrogen abstraction, and subsequent branching or scission. Topologies are distinguished by chain ends, number of branches, and number of reactive ends. The resulting time dependent trivariate distribution is utilized to extract various distributive properties of the polymer. The results exhibit excellent agreement with data from Monte Carlo simulations
I. Kryven, PD. Iedema.
Predicting multidimensional distributive properties of hyperbranched polymer resulting from AB2 polymerization with substitution, cyclization and shielding,
Volume 54, Issue 14, Pages 3472–3484, 2013
A deterministic mathematical model for the polymerization of hyperbranched molecules accounting for substitution, cyclization, and shielding effect has been developed as a system of nonlinear population balances. The solution obtained by a novel approximation method shows perfect agreement with the analytical solution in limiting cases and provides, for the first time in this class of polymerization problems, full multidimensional results.
I. Kryven, A. Berkenbos, P. Melo, DM. Kim. PD. Iedema.
Modeling Crosslinking Polymerization in Batch and Continuous Reactors,
Volume 7, Issue 5, pages 205–220, 2013
A new pseudo-distribution approach is applied to the modeling of crosslinking copolymerization of vinyl and divinyl monomer and compared to Monte Carlo (MC) simulations. With the number of free pending double bonds as the main distribution variable, a rigorous solution of the three leading moments of the molecular size distribution becomes possible. Validation takes place with data of methyl methacrylate with ethylene glycol dimethacrylate. Well within the sol regime perfect agreement is found, but near the gelpoint larger discrepancies do appear. This is probably due to the existence of multiradicals that are not taken into account in the population balance approaches.
T. van der Aalst, D. Denteneer, H. Döring, MH. Duong, RJ. Kang, M. Keane, J. Kool, I. Kryven, T. Meyfroyt, T. Müller, G. Regts, J. Tomczyk
The random disc thrower problem,
Proceedings SWI 2013, Pages 59-78, 2013
We describe a number of approaches to a question posed by Philips Research, described as the "random disc thrower" problem. Given a square grid of points in the plane, we cover the points by equal-sized planar discs according to the following random process. At each step, a random point of the grid is chosen from the set of uncovered points as the centre of a new disc. This is an abstract model of spatial reuse in wireless networks. A question of Philips Research asks what, as a function of the grid length, is the expected number of discs chosen before the process can no longer continue? Our main results concern the one-dimensional variant of this problem, which can be solved reasonably well, though we also provide a number of approaches towards an approximate solution of the original two-dimensional problem. The two-dimensional problem is related to an old, unresolved conjecture () that has been the object of close study in both probability theory and statistical physics. Keywords: generating functions, Markov random fields, random sequential adsorption, Rényi’s parking problem, wireless networks
V. Kukharskyy, Ya. Savula, I. Kryven
Modified method of residual-free bubbles for solving the advection-diffusion problem with high Peclet number,
Series Appl. Math. and Informatics. Visnyk of the Lviv University, Volum 20, Pages 85-94, 2013
The numerical scheme based on the residual free bubbles approach and the hierarchy basis discretization for advection-diffusion problems with dominated advection is introduced. Among properties of the developed method are better stability to oscillations for hight Peclet numbers, better time performance, and simplicity in parallel computing application. The computational analysis of convergence and time performance on an example of a 2D symmetric advection-diffusion problem for 10e10 Peclet number is performed.
I. Kryven, PD. Iedema.
A Novel Approach to Population Balance Modeling of Reactive Polymer Modification Leading to Branching,
Volume 22, Issue 2, pages 89–106, 2013
The mathematical treatment of polymer modification systems, described by population balances containing convolution is discussed. The two-dimensional case (molecular weight vs. number of branch points) was considered by utilizing approximations of distributions, expanding them in terms of Gaussian basis functions. Three branching reactions were addressed: chain backbone to chain end point coupling; three-functional coupling of chain ends; and crosslinking. The results were compared to those of Monte Carlo (MC) simulations. Good agreement was observed, although the quality of a distribution as generated by the numerical approach is much better in view of the strong scatter in the MC data.
J.B. van den Berg, R. Castro, J. Draisma, J. Evers, M. Hendriks, O. Krehel, I. Kryven, K. Mora, B. Szabó, P. Zwiernik.
Non-imaging Optics for LED-Lighting,
Proceedings of SWI 2012, Editor MAA. Boon, ISBN 978-90-6464-630-0, Pages 70-103, 2013
In this report, several methods are investigated to rapidly compute the light intensity function, either in the far field or on a finite-distance screen, of light emanating from a light fixture with a given shape. Different shapes are considered, namely polygonal and (piecewise) smooth. In the first case, analytic methods are sought to circumvent the use of Monte Carlo methods and ray-tracing with large sample size. In the second case, refinements of the Monte Carlo method (notably using a bootstrap procedure) are devised to minimize the number of samples needed for a good approximation of the intensity function.
W. Kager, I. Kryven, K. Myerscough, T. van Opstal, T. Rot.
Statistical Modelling of Pre-Impact Velocities in Car Crashes,
Proceedings SWI 2011, Pages 133-148, 2013
The law wants to determine if any party involved in a car crash is guilty. The Dutch court invokes the expertise of the Netherlands Forensic Institute (NFI) to answer this question. We discuss the present method of the NFI to determine probabilities on pre-impact car velocities, given the evidence from the crash scene. A disadvantage of this method is that it requires a prior distribution on the velocities of the cars involved in the crash. We suggest a different approach, that of statistical significance testing, which can be carried out without a prior. We explain this method, and apply it to a toy model. Finally, a sensitivity analysis is performed on a simple two-car collision model.