Overview presentation on functionalities offered by the CRISMA framework for building of the crisis management decision support applications. The focus is at re-usable concepts and few concrete functions which were shown in the workshop later on.
Models Done Better... - UDG2018 - Intertek and DHIStephen Flood
Use of integrator systems (operational data and model management platforms) to enhance model performance and value.
Presented at the CIWEM Urban Drainage Group Annual Conference 2018
Richard Dannatt - Intertek
Steve Flood - DHI
Cloud computing business framework
Victor Chang, Leeds Beckett University
International conference on
“DATA, DIGITAL BUSINESS MODELS, CLOUD COMPUTING AND ORGANIZATIONAL DESIGN”
24-25 November 2014 ,
Université Paris –Sud
Highway to heaven - Microservices Meetup MunichChristian Deger
Fed up with stop and go in your data center? Why not shift into overdrive and pull into the fast lane? Learn how AutoScout24 are building their Autobahn in the cloud to become the market leader in Europe's vehicle classified business.
Reinventing themselves by making a radical transition from monoliths to microservices, from .NET on Windows to Scala on Linux, from data center to AWS and from built by devs and run by ops to a devops mindset.
While the current stack keeps running, ever more microservices will go live as you listen to stories from the trenches.
Key takeaways from this talk includes: How to...
… become cloud native
… evolve the architecture
… create “you build it you run it” teams
… involve business people in the transformation
Created and presented together with Wolf Schleger (ThoughtWorks)
Models Done Better... - UDG2018 - Intertek and DHIStephen Flood
Use of integrator systems (operational data and model management platforms) to enhance model performance and value.
Presented at the CIWEM Urban Drainage Group Annual Conference 2018
Richard Dannatt - Intertek
Steve Flood - DHI
Cloud computing business framework
Victor Chang, Leeds Beckett University
International conference on
“DATA, DIGITAL BUSINESS MODELS, CLOUD COMPUTING AND ORGANIZATIONAL DESIGN”
24-25 November 2014 ,
Université Paris –Sud
Highway to heaven - Microservices Meetup MunichChristian Deger
Fed up with stop and go in your data center? Why not shift into overdrive and pull into the fast lane? Learn how AutoScout24 are building their Autobahn in the cloud to become the market leader in Europe's vehicle classified business.
Reinventing themselves by making a radical transition from monoliths to microservices, from .NET on Windows to Scala on Linux, from data center to AWS and from built by devs and run by ops to a devops mindset.
While the current stack keeps running, ever more microservices will go live as you listen to stories from the trenches.
Key takeaways from this talk includes: How to...
… become cloud native
… evolve the architecture
… create “you build it you run it” teams
… involve business people in the transformation
Created and presented together with Wolf Schleger (ThoughtWorks)
Taufik kurniawan strategy and approach to private cloud infrastructure impl...teknologiinformasi
Loosely Coupled Tightly Integrated Approach
PROs
Based on Open standard technology
Less Vendor Lock-in
More Flexible to Vendor/Technology choice
Comprehend and Understand the Technology better
Relatively lower CAPEX
CONs
More efforts and resources to implement, operate and maintain
Relatively higher OPEX
System Data Repository
Presented at the 8th ESA Workshop on Avionics, Data, Control and Software Systems (ADCSS'14)
from Oct. 27, 2014 till Oct. 29, 2014
DICE project defines a quality-driven development methodology and related tools that will markedly accelerate the development of business-critical data-intensive applications running on public or private clouds. A quality engineering toolchain offering simulation, verification, and numerical optimisation will leverage these extensions to drive the early design stages of the application development and guide software quality evolution. DevOps-inspired methods for deployment, testing, continuous integration and monitoring feedback analysis will be used to accelerate the incorporation of quality in data-intensive cloud application.
Surrogate Model-Based Reliability Analysis of Composite UAV Wing facilitation...Altair
Numerical simulation becomes increasingly strategic to design innovative products and to set up their manufacturing processes, reducing simultaneously development costs and time to market while increasing quality and reliability.
To support this evolution, SILKAN develops a platform for the integration of various types of simulation software, named BUILDERTM.
BUILDERTM is an efficient, innovative and scalable simulation-based platform designed to deal with the increasing use of complex numerical simulations applied to part design, system design or manufacturing processes.
The principal objectives of this platform are to:
Promote and structure the use of simulation
Standardize, parameterize and automate simulation processes.
Capture and re-use the best practices.
Facilitate coupling between different simulation levels and tools.
Improve collaboration across different project teams.
Facilitate access to simulation means for the uninitiated.
Accelerate design and production cycles.
Democratize the use of optimization and reliability procedures and better control manufacturing processes and failure risks.
An application example using BUILDERTM is addressed in this paper. It deals with the robust design of a composite UAV wing. The associated simulation workflow includes two principal steps.
During the first step, Matlab is used to estimate aerodynamic loads applied to the wing when as a function of flight parameters: air flow speed, angle of attack of the wing and aileron deflection angles. A Design of Experiment (DoE) is built by varying the flight parameters in order to cover all the flight domain of the UAV.
The aerodynamic loads thus obtained are then injected into OptiStruct to estimate Tsai-Wu failure criteria for the composite material. An efficient surrogate model is then built from the obtained Tasi-Wu criteria and covers the entire flight domain. Finally to conclude this first part, a failure probability , based on Tsai-Wu criteria, is estimated using the produced surrogate model.
In the second step the following optimization problem is defined using some design variables of the wing (essentially thicknesses of composite layers of the wing):
Wing Mass is calculated by Optistruct, and being evaluated using the step1. An evolutionary algorithm implemented into Dakota is used to perform this surrogate-model -
based optimization.
The set up, parameterization and automation of this complex simulation workflow is facilitated and achieved through the use of the BUILDERTM platform. The combination of different software at different levels of the workflow is also made accessible by the use of BUILDERTM.
Speakers
Samir Ben Chaabane, Numerical Simulation Manager for EMEA, SILKAN S.A
Transparency and Contracts: Continuous Integration and Delivery in the Automo...Eric Knauss
This is our presentation at ICSE 2018 SEIP Track on Transparency and Contracts in the Context of Continuous Integration and Delivery in the Automotive Ecosystem
A presentation given to DTIC on December 15, 2010 highlighting the findings of their virtual worlds vision paper, looking at some of their potential use cases, and offering suggestions to potential technology platforms.
Recent IAM presentation by Dr J Hagan of Severn Trent Water, providing an overview of the modelling process STW go through for regulatory planning within the water sector.
Taufik kurniawan strategy and approach to private cloud infrastructure impl...teknologiinformasi
Loosely Coupled Tightly Integrated Approach
PROs
Based on Open standard technology
Less Vendor Lock-in
More Flexible to Vendor/Technology choice
Comprehend and Understand the Technology better
Relatively lower CAPEX
CONs
More efforts and resources to implement, operate and maintain
Relatively higher OPEX
System Data Repository
Presented at the 8th ESA Workshop on Avionics, Data, Control and Software Systems (ADCSS'14)
from Oct. 27, 2014 till Oct. 29, 2014
DICE project defines a quality-driven development methodology and related tools that will markedly accelerate the development of business-critical data-intensive applications running on public or private clouds. A quality engineering toolchain offering simulation, verification, and numerical optimisation will leverage these extensions to drive the early design stages of the application development and guide software quality evolution. DevOps-inspired methods for deployment, testing, continuous integration and monitoring feedback analysis will be used to accelerate the incorporation of quality in data-intensive cloud application.
Surrogate Model-Based Reliability Analysis of Composite UAV Wing facilitation...Altair
Numerical simulation becomes increasingly strategic to design innovative products and to set up their manufacturing processes, reducing simultaneously development costs and time to market while increasing quality and reliability.
To support this evolution, SILKAN develops a platform for the integration of various types of simulation software, named BUILDERTM.
BUILDERTM is an efficient, innovative and scalable simulation-based platform designed to deal with the increasing use of complex numerical simulations applied to part design, system design or manufacturing processes.
The principal objectives of this platform are to:
Promote and structure the use of simulation
Standardize, parameterize and automate simulation processes.
Capture and re-use the best practices.
Facilitate coupling between different simulation levels and tools.
Improve collaboration across different project teams.
Facilitate access to simulation means for the uninitiated.
Accelerate design and production cycles.
Democratize the use of optimization and reliability procedures and better control manufacturing processes and failure risks.
An application example using BUILDERTM is addressed in this paper. It deals with the robust design of a composite UAV wing. The associated simulation workflow includes two principal steps.
During the first step, Matlab is used to estimate aerodynamic loads applied to the wing when as a function of flight parameters: air flow speed, angle of attack of the wing and aileron deflection angles. A Design of Experiment (DoE) is built by varying the flight parameters in order to cover all the flight domain of the UAV.
The aerodynamic loads thus obtained are then injected into OptiStruct to estimate Tsai-Wu failure criteria for the composite material. An efficient surrogate model is then built from the obtained Tasi-Wu criteria and covers the entire flight domain. Finally to conclude this first part, a failure probability , based on Tsai-Wu criteria, is estimated using the produced surrogate model.
In the second step the following optimization problem is defined using some design variables of the wing (essentially thicknesses of composite layers of the wing):
Wing Mass is calculated by Optistruct, and being evaluated using the step1. An evolutionary algorithm implemented into Dakota is used to perform this surrogate-model -
based optimization.
The set up, parameterization and automation of this complex simulation workflow is facilitated and achieved through the use of the BUILDERTM platform. The combination of different software at different levels of the workflow is also made accessible by the use of BUILDERTM.
Speakers
Samir Ben Chaabane, Numerical Simulation Manager for EMEA, SILKAN S.A
Transparency and Contracts: Continuous Integration and Delivery in the Automo...Eric Knauss
This is our presentation at ICSE 2018 SEIP Track on Transparency and Contracts in the Context of Continuous Integration and Delivery in the Automotive Ecosystem
A presentation given to DTIC on December 15, 2010 highlighting the findings of their virtual worlds vision paper, looking at some of their potential use cases, and offering suggestions to potential technology platforms.
Recent IAM presentation by Dr J Hagan of Severn Trent Water, providing an overview of the modelling process STW go through for regulatory planning within the water sector.
Similar to 2014 05 CRISMA architecture for transferable applications (20)
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
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In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
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While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
2014 05 CRISMA architecture for transferable applications
1. Modelling crisis management for improved action and preparedness
An Architecture for transferable
applications
CRISMA end user workshop at PSCE conference
2014-05-22, Göteborg, Se
Denis Havlik (AIT), Pascal Dihé (cismet)
This project has received funding from the European Union’s Seventh Framework Programme for research,
technological development and demonstration under grant agreement no 284552 "CRISMA“
2. 15/10/2014 | 2
We can only develop a
few applications at the
level of “working
prototype”
Denis Havlik, AIT and Pascal Dihé, cismet
So why should you think
about CRISMA
framework, building
blocks and architecture?
And why do we claim
that CRISMA results
are “transferable”?
3. 15/10/2014 | 3
Denis Havlik, AIT and Pascal Dihé, cismet
Intended uses of CRISMA
Debriefing
(Desktop) Training
for decision makers
Planning - Infrastructure
- Resources
4. 15/10/2014 | 4
CRISMA applications – topical coverage
Nordic
exposure
Denis Havlik, AIT and Pascal Dihé, cismet
Coastal
inundation
Toxic gas
exposure
Earthquake,
cascading
effects
Mass
accident
Optimization
of RM
planning
X ~ ~ ~ X
Decision
maker
training
~ X ~
Investment
planning ~ X X
Debriefing ~ ~ X
X = major interest; ~ = nice to have & possible extensions; RM = resource management
5. 15/10/2014 | 5
CRISMA assumption: these
applications can be designed in
Denis Havlik, AIT and Pascal Dihé, cismet
coherent way
=> re-use of concepts and
software; transferable to new
applications
6. 15/10/2014 | 6
Concept => implementation => applications
Denis Havlik, AIT and Pascal Dihé, cismet
Specification
Level
Implementation
Level
“CRISMA framework architecture v2” document can be downloaded from our web site
7. 15/10/2014 | 7
Events => decisions => consequences
Any element can be
either real or
simulated
Denis Havlik, AIT and Pascal Dihé, cismet
Outcome can be
changed by users
decisions.
Behind the
scenes, “things
happen”
8. 15/10/2014 | 8
Common conceptual business logic
Parameters Parameters Parameters
Denis Havlik, AIT and Pascal Dihé, cismet
OR OR OR
Define freely Define freely Define freely
(what is out here?)
World
World
Model
Incident
Model
Response
Model
World
Situation(X, t)
Incident
Situation(X, t)
(what are we dealing with?) (how do we react?)
influences Incident influences Response
creates Parameters
Restore
Model
Restore
Situation(X, t)
Response
Situation(X, t)
Define freely
The „world“ is
represented by „situation“
and by models which can
change the situation
Situations and models
pertinent to different stages
of crisis management are
relatively decoupled…
New situations
can also be
postulated by
users
9. 15/10/2014 | 9
Materialization of World states, decisions, transitions
World State Simulation
Situation Maps
Vulnerability
Classes
:
Objects of
Interest
Weather Data
...
Simulation
Control
Parameter
Denis Havlik, AIT and Pascal Dihé, cismet
Simulation
Simulation
M
M
Manipulation
World State'
Situation Maps
Vulnerability
Classes
:
Objects of
Interest
Weather Data
...
Simulation
Control
Parameter
change
Indicators
Indicator
Function
Indicators
Simulation
. . .
trigger
calculate
perform
Hazard Exposure
kl
Mitigation
Resource
Managem
ent
f
M
M
CRISMA
framework
operate on
„world states“,
coherent sets
of data
describing the
(simulated)
world
Users Decisions
change the world state
– either directly or by
changing model
parameters
Everything we
know about the
World is based
on the world
state
10. 15/10/2014 | 10
Concept of Decision Points & Alternative Worlds
World State
Data
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Denis Havlik, AIT and Pascal Dihé, cismet
World
State
Simulation
Model Control
Parameter
Criteria and Costs
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
World State
Transition
Time
Alternatives
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Alternative users’
decisions result in
alternative World
States.
The results can be
compared...
11. 15/10/2014 | 11
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Simulation
Model Control
Parameter
Criteria and Costs
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Denis Havlik, AIT and Pascal Dihé, cismet
World State
Data
World
State
World
State
World
State
World
State
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Simulation
Model Control
Parameter
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Criteria and Costs
Planning
Decision
Making
Training
Comparison through
indicators and criteria
functions
Indicators and Criteria
are representative
quantifications of a world
state
Are independent from the
models and decisions
are the base for situation
analysis and visualization
support decision making
Transferable solutions can be
developed
12. 15/10/2014 | 14
And some transferable models…
Denis Havlik, AIT and Pascal Dihé, cismet
ECONOMIC
IMPACTS
CASCADE
EFFECTS
TIME
DEPENDENT
VULNERABILITY
RESSOURCES
DEPLOYMENT
Illustrations by: Konzumel (money - http://www.flickr.com/photos/kozumel/), Jeff McNeill (time - http://www.flickr.com/photos/jeffmcneill/),
Donwoodyard (ambulance - http://commons.wikimedia.org/wiki/File:Lanka_ambulance.jpg),
Nauticashades (domino - http://commons.wikimedia.org/wiki/File%3ADomino_Cascade.JPG)
13. 15/10/2014 | 15
Sure, this sounds good
at the level of power
point presentation…
Denis Havlik, AIT and Pascal Dihé, cismet
But…
.. can you show us
any actual evidence?
14. 15/10/2014 | 16
Denis Havlik, AIT and Pascal Dihé, cismet
YES we can!
(but we are quite scared because of the internet
connectivity issues we experienced last week)
15. 15/10/2014 | 17
Denis Havlik, AIT and Pascal Dihé, cismet
We will present two working
prototypes as they are today next: one
related to infrastructure planning,
other to resource management
training
Both follow the CRISMA
architectural principles
and already share big
part of the software…
16. 15/10/2014 | 19
Three illustrative
Denis Havlik, AIT and Pascal Dihé, cismet
examples:
17. 15/10/2014 | 20
Denis Havlik, AIT and Pascal Dihé, cismet
Indicator analysis and
multi-criteria functions
and GUI elements
1
18. 15/10/2014 | 21
What is the relative importance of…?
Denis Havlik, AIT and Pascal Dihé, cismet
Illustrations from wikimedia.org
19. 15/10/2014 | 22
Handling of cascading
Denis Havlik, AIT and Pascal Dihé, cismet
events
issue: probabilities are often
unknown
2
21. 15/10/2014 | 24
Denis Havlik, AIT and Pascal Dihé, cismet
Transferability
between “training” and
“planning” pilots
demonstration planned in v2
3
22. 15/10/2014 | 25
Why and how can we achieve this?
With fully-fledged Pilot C (Israel) application, one could
already validate a plan by executing it as a training.
not a very user-friendly solution
=> we shall create additional v2 Building Block to:
1. Track decisions (as they reflect the plan) from a training run
– This information is already available
2. replay with some variations in environment, e.g. number of
patients, weather conditions
3. replay with altered decisions (testing some changes in the
response plan)
Denis Havlik, AIT and Pascal Dihé, cismet
23. 15/10/2014 | 26
Resource management training and planning:
Denis Havlik, AIT and Pascal Dihé, cismet
synergies and differences
1) Training 2) Planning Differences & comments
Scenario setup X X -
Interactive view X x Not strictly necessary, but we shall
use interactive view to prepare initial
plans
Store decisions X X
Edit decisions - X Changing parameters (e.g. when and
where to send resources?)
Edit initial
parameters
X X part of scenario setup! (accident
position, weather, no. victims…)
Re-play decisions x X Nice to have in training case („demo
mode“)
Result
comparison
X X -
24. 15/10/2014 | 27
Denis Havlik, AIT and Pascal Dihé, cismet
Thank You!
Follow CRISMA in: www.crismaproject.eu